TL;DR: Onchain credit company Ibis emerged from stealth on October 28, announcing a $250 million credit facility with FalconX and a pre-seed funding round. For a crypto market accustomed to cycles of unsecured or poorly understood lending, the phrase institutional credit needs to be earned.
Onchain credit company Ibis emerged from stealth on October 28, announcing a $250 million credit facility with FalconX and a pre-seed funding round. The company says its initial borrowers will include eligible firms active in crypto trading and capital markets. Anchorage Digital Bank is named as a custody, banking and design partner, with other investors and advisers supporting the business. A committed credit facility defines potential lending capacity; it should not be reported as $250 million of loans already originated or as the company’s cash revenue.
The event and the market response
Ibis plans to originate, structure, tokenize, service and manage risk for institutional credit agreements. Its pitch is that digital-asset trading businesses can have sophisticated revenue and collateral profiles while conventional lenders lack frameworks to evaluate them. Combining underwriting with tokenized records may make credit positions easier to track or distribute to capital providers, but the economic risk does not disappear when documents become digital. The borrower’s ability to repay, enforceable collateral arrangements and a lender’s rights in default remain the basis of the product.
Why the development matters to the crypto market
For a crypto market accustomed to cycles of unsecured or poorly understood lending, the phrase institutional credit needs to be earned. A $250 million headline may suggest confidence, but lending discipline depends on covenants, concentration limits and transparent collateral controls when markets fall. Ibis’s structure could support a more professional market if those protections work in practice. The key distinction is between credit availability as an announcement and durable repayment performance through a stressful trading environment.
Tokenized finance is often described as a single market, but it covers quite different instruments: cash-like balances, securities, private credit and other claims. Each has different settlement and counterparty risks. Institutional adoption becomes meaningful when service providers can explain who owes what, how a holder exits a position and what happens during a dispute. The detail matters as much as speed. A sound launch can be the beginning of a larger change, although the step from successful integration to widespread, economically useful activity is rarely automatic.
The distinction between a blockchain record and the economic rights behind it is crucial for anyone evaluating this news. Digital tokens may move quickly, but title, custody, investor eligibility and redemption remain governed by legal agreements and regulated entities. A new integration should therefore be judged by the processes it can complete end to end, not simply by the number of assets it can represent. Traders also need to resist treating institutional enthusiasm as an automatic bullish signal for a native cryptocurrency: commercial adoption and token pricing can diverge for long periods.
What the headline does not establish
The press release says the platform may expand beyond crypto markets into other capital-hungry technology segments, including computing infrastructure and robotics. Those ambitions are not the same as live lending programs in each field. The confirmed starting point is the FalconX facility, the backing of named partners and Ibis’s proposed credit platform. Important details not fully specified in the announcement include loan pricing, advance rates, eligibility tests, actual utilization and how a tokenized claim would behave under insolvency. Institutions will demand clarity on those issues.
What to watch next
Track how much of the facility is drawn, the types of collateral accepted and evidence of repayments or portfolio performance. Those details will establish whether the structure becomes a repeatable market rather than an attractive launch headline.
TL;DR: Movantis and the Stellar Development Foundation announced on October 29 that Stellar will become a settlement option in the payments company’s multi-rail network. For Stellar watchers, this is the sort of story where day-to-day usage matters more than an abstract partnership total.
Movantis and the Stellar Development Foundation announced on October 29 that Stellar will become a settlement option in the payments company’s multi-rail network. The initial corridor focuses on USDC settlement for transfers originating in the United States and moving toward recipients in El Salvador. Movantis supplies connections to regulated local partners, foreign-exchange conversion where required and last-mile payout services. This is a specific payments integration, not a claim that all of the company’s traffic has shifted to stablecoins or that every customer will be required to use cryptocurrency.
The event and the market response
The distinction between the settlement leg and the customer-facing payout is central. Stablecoins can move value between service providers outside bank opening hours, but recipients generally need usable local money or an account they recognize. Movantis says its platform already handles more than $60 billion annually across more than 200 million transactions and a network of over 90,000 payout locations. Those figures describe the existing business, not volumes on Stellar. The integration is intended to connect a new digital rail with that established distribution footprint.
Why the development matters to the crypto market
For Stellar watchers, this is the sort of story where day-to-day usage matters more than an abstract partnership total. A recognizable payment company is adding USDC settlement to an established corridor, giving analysts a concrete route to monitor. Nonetheless, the volume currently passing over Stellar has not been disclosed. Any projections for XLM based on Movantis’s overall annual transaction figures would be misleading. The real test is whether customers and payment firms see faster, cheaper and more dependable transfers after all offchain steps are included.
A cross-border payment has at least two meanings of speed: how quickly value moves between institutions, and how quickly the recipient can spend it. Stablecoin settlement can improve the first without necessarily solving the second. Real-world payouts require local networks, liquidity, compliance screening and customer support. The strongest payment partnerships join those pieces rather than attempting to replace everything with one blockchain. Readers should look for end-to-end performance data and distinguish existing network size from transaction volume that actually uses a newly announced digital rail.
Large payment systems are built around reliability and accountability. Institutions need proof that a transfer can be traced, reconciled, disputed where appropriate and settled within their regulatory obligations. Programmable assets may create efficiencies, but they also demand carefully designed exception handling when a recipient cannot be paid or a conversion fails. It is not enough for a blockchain transaction to reach finality. A customer judges the complete service. That makes local distribution and operational integration central to the commercial case for stablecoin payments.
What the headline does not establish
A cross-border payment chain remains only as strong as its slowest regulated or operational link. Licensing, source-of-funds checks, exchange rates, transaction screening and the ability to deliver final funds determine whether customers receive the promised experience. Movantis describes further business and consumer corridors as potential extensions, but the confirmed starting point is US-to-El Salvador. The announced capacity of an underlying blockchain says little about actual fees or completion times for a transfer that also crosses traditional payment networks.
What to watch next
The useful next figures are live USDC settlement volumes in the first corridor, end-to-end costs and payout completion rates. Expansion to additional markets would be meaningful once the original route shows repeatable results.
TL;DR: Pontoro and Archax have announced the launch of an Automated Liquidity Pool on Stellar during Meridian 2026. The strongest market lesson is to separate token supply from genuine tradable liquidity.
Pontoro and Archax have announced the launch of an Automated Liquidity Pool on Stellar during Meridian 2026. Their pilot combines liquid money-market assets with private-market fund exposure in a structure that uses predefined pricing and allocation rules to manage liquidity. Archax supplies regulated tokenization and issuance of permissioned interests, while Pontoro provides the model and operating infrastructure. The aim is to make private-asset exposure easier to distribute and manage, not to turn every illiquid holding into instantly redeemable cash.
The event and the market response
Private investments commonly offer longer holding periods and fewer opportunities to exit than listed securities. That creates a mismatch when an investor wants liquidity while the underlying manager needs stable capital. Pontoro’s design attempts to address the mismatch within a pool holding liquid and less-liquid investments, with rules that adjust incentives as redemptions or subscriptions change its composition. The model depends on actual available liquid assets, credible valuations and a clearly disclosed process for handling stress. A token representing the pool does not by itself make private loans or funds more liquid.
Why the development matters to the crypto market
The strongest market lesson is to separate token supply from genuine tradable liquidity. Digital ownership records can simplify transfer or reporting, but cannot guarantee that buyers exist at a fair price during a downturn. Pontoro’s rules-based approach explicitly acknowledges that problem by making available liquidity and incentives part of the product. For tokenization enthusiasts, it is a more useful development than a headline about a large notional amount moved onchain, because it tackles how investors might actually enter and leave positions.
Tokenized finance is often described as a single market, but it covers quite different instruments: cash-like balances, securities, private credit and other claims. Each has different settlement and counterparty risks. Institutional adoption becomes meaningful when service providers can explain who owes what, how a holder exits a position and what happens during a dispute. The detail matters as much as speed. A sound launch can be the beginning of a larger change, although the step from successful integration to widespread, economically useful activity is rarely automatic.
The distinction between a blockchain record and the economic rights behind it is crucial for anyone evaluating this news. Digital tokens may move quickly, but title, custody, investor eligibility and redemption remain governed by legal agreements and regulated entities. A new integration should therefore be judged by the processes it can complete end to end, not simply by the number of assets it can represent. Traders also need to resist treating institutional enthusiasm as an automatic bullish signal for a native cryptocurrency: commercial adoption and token pricing can diverge for long periods.
What the headline does not establish
The release says the pool interests are issued as permissioned tokens on Stellar and held in identity-verified wallets. The fund manager retains authority over selection, valuation and governance. This is a material qualification: the digital wrapper does not replace asset-management decisions or investor eligibility requirements. The Stellar Development Foundation also disclosed that it is an investor in both Pontoro and Archax, context that should accompany accounts of the partnership. A functioning pilot can demonstrate mechanics, but sustained investor use and performance under withdrawal pressure remain unproven.
What to watch next
Future pilot reports should reveal redemption outcomes, subscription volumes and how the pool responds to stressed markets. Without that information it would be premature to claim that a lasting liquid secondary market for private assets has been created.
TL;DR: Tokenization platform Securitize announced plans on October 28 to integrate the Stellar network into the infrastructure it offers institutional asset managers. For market participants following XLM, the news provides an institutional adoption narrative but no automatic revenue calculation for the network’s native asset.
Tokenization platform Securitize announced plans on October 28 to integrate the Stellar network into the infrastructure it offers institutional asset managers. The company says the connection will support future issuance and management of tokenized financial assets, extending choices for clients bringing traditional products onto blockchains. The announcement was made during Meridian 2026 in Lisbon. It describes an intended integration, not the immediate launch of a named new fund, and the firms have said further asset-level details will be released later.
The event and the market response
Securitize operates in a part of the market where the token is only one layer of the product. Issuers must also organize investor eligibility, ownership records, subscriptions, redemptions and ongoing regulatory obligations. Stellar offers asset issuance and transfer functionality along with features that can support regulated controls. Its existing ecosystem includes financial-asset initiatives and cross-border payment providers. The proposed combination is designed to give managers more flexibility in choosing networks that match a particular distribution and operating model.
Why the development matters to the crypto market
For market participants following XLM, the news provides an institutional adoption narrative but no automatic revenue calculation for the network’s native asset. A manager may choose Stellar because of operational attributes while end investors hold tokenized securities rather than buying XLM for exposure. What would strengthen the story is a named live issuance, measurable assets, and secondary workflows that show the integration is being used. The announcement highlights growing competition for institutional tokenization activity across public and controlled networks.
An institutional buyer will evaluate the cost of connecting a new rail to its existing systems before celebrating the technology. That includes identity checks, transaction reporting, asset servicing, reconciliation and recovery procedures when something goes wrong. A smaller but repeatable workflow can be commercially more valuable than an enormous theoretical market size. In this case, progress should be measured against the promised operational improvement and the conditions attached to it. Without usage figures, no one can reliably turn a partnership or infrastructure milestone into a forecast of investment returns.
Tokenized finance is often described as a single market, but it covers quite different instruments: cash-like balances, securities, private credit and other claims. Each has different settlement and counterparty risks. Institutional adoption becomes meaningful when service providers can explain who owes what, how a holder exits a position and what happens during a dispute. The detail matters as much as speed. A sound launch can be the beginning of a larger change, although the step from successful integration to widespread, economically useful activity is rarely automatic.
What the headline does not establish
It is important not to equate a new blockchain option with unrestricted secondary-market trading. Tokenized shares in regulated funds may remain available only to approved investors, with transfers and settlement subject to rules. Fees, custody choices, liquidity and interoperability will matter as much as the chain itself. Securitize did not announce a launch date for any specific Stellar-issued product in this release. The milestone is the planned expansion of institutional infrastructure rather than a complete account of the products that will eventually use it.
What to watch next
The firms have not named the first Stellar-based product. That announcement, together with an operational timetable and evidence of real subscriptions or redemptions, is the logical next checkpoint for this story.
TL;DR: At its Swell conference, Ripple said it was approaching a $900 million annualized product-revenue run rate as it heads toward the end of 2026. For cryptocurrency markets, the announcement is another example of major blockchain companies finding revenue streams beyond token price appreciation.
At its Swell conference, Ripple said it was approaching a $900 million annualized product-revenue run rate as it heads toward the end of 2026. The company links the expansion to stronger enterprise demand and the integration of acquisitions across payments, custody, prime brokerage and treasury management. It also highlighted relationships involving BNY, Robinhood, DriveWealth and other organizations. A run rate is an annualized pace derived from a current period; it is not the same as audited full-year revenue or a guarantee that the pace will be maintained.
The event and the market response
Ripple says its products enabled more than $16 trillion in transactions during 2025 and that more than 1,700 institutions, corporates and enterprises have access to its digital-asset infrastructure. Those figures describe activity and reach across a broad product portfolio rather than direct XRP trading volumes. The company is using the same conference to emphasize RLUSD, its bank-charter progress and efforts to join conventional financial workflows with onchain assets. Each component addresses a different part of the business case, from asset custody to corporate cash movement.
Why the development matters to the crypto market
For cryptocurrency markets, the announcement is another example of major blockchain companies finding revenue streams beyond token price appreciation. Payments infrastructure, custody and regulated stablecoins can serve clients even when speculative trading cools. However, the relationship between a company’s business revenue and the price of a separate public-network asset is indirect. The most useful market signals will be demonstrable demand for XRP Ledger transactions, stablecoin settlement and institutional integrations, rather than assuming all corporate growth flows to XRP holders.
The distinction between a blockchain record and the economic rights behind it is crucial for anyone evaluating this news. Digital tokens may move quickly, but title, custody, investor eligibility and redemption remain governed by legal agreements and regulated entities. A new integration should therefore be judged by the processes it can complete end to end, not simply by the number of assets it can represent. Traders also need to resist treating institutional enthusiasm as an automatic bullish signal for a native cryptocurrency: commercial adoption and token pricing can diverge for long periods.
An institutional buyer will evaluate the cost of connecting a new rail to its existing systems before celebrating the technology. That includes identity checks, transaction reporting, asset servicing, reconciliation and recovery procedures when something goes wrong. A smaller but repeatable workflow can be commercially more valuable than an enormous theoretical market size. In this case, progress should be measured against the promised operational improvement and the conditions attached to it. Without usage figures, no one can reliably turn a partnership or infrastructure milestone into a forecast of investment returns.
What the headline does not establish
The bigger question is how announcements translate into recurring revenue and transaction activity. A partnership may include integration work, testing or planned expansion before it represents substantial production volume. The economics of corporate treasury software are also different from those of token trading or settlement. Investors should therefore avoid treating the headline run rate as a proxy for the XRP token’s intrinsic value. Ripple’s disclosure offers direction about strategy, but does not replace segment-by-segment financial statements.
What to watch next
Future results should clarify the difference between announced partnerships, active customers and recognized revenue. Independent evidence of settlement volume and adoption across multiple products would give the annualized figure greater meaning.
Chainlink launches Chainlink 24/7, a pricing service covering weekends and holidays for stocks, commodities and other traditional assets.
Off-hours prices are based on quotes from perpetual futures venues, not closed exchanges.
Aave is the first partner, using the feeds on its institutional Horizon platform.
Chainlink says its weekday infrastructure already covers more than $1.6 billion in tokenized stocks.
Blockchain markets run around the clock, but the assets many of them track do not. Stock exchanges close at night, on weekends, and on holidays, leaving on-chain applications without a reliable price.
Until now, protocols had a few poor options: freeze markets, rely on the last known price, or build their own valuation tools. Chainlink 24/7 aims to remove that problem by supplying one continuous price series per asset.
How Chainlink 24/7 Works
The service blends two sources. When traditional markets are open, it uses prices from regular and extended sessions. When they shut, it switches to an off-hours reference built from perpetual futures quotes.
Chainlink says the system pulls quotes from multiple futures venues, removes stale inputs and limits the influence of outliers. Importantly, the weekend price reflects derivatives trading rather than actual transactions on closed exchanges.
Lending protocols can read prices published directly onchain through Data Feeds. Trading platforms and prediction markets can use Data Streams for faster updates, which also flag the current market session so apps can adjust risk settings.
Aave Horizon Adopts the Feeds
Aave is the launch partner, integrating the feeds into Horizon, its lending platform for institutions. Horizon lets qualified investors borrow against tokenized assets, and the rollout begins with tokenized versions of heavily traded US stocks.
Reliable weekend prices matter for lenders because collateral values need to stay current to manage liquidation risk, even when stock exchanges are offline.
Building on Earlier Pricing Products
The launch follows Chainlink’s January debut of 24/5 pricing for US stocks and ETFs, which covered pre-market, regular, post-market and overnight sessions. The company says that weekday infrastructure now supports over $1.6 billion in tokenized stocks.
With the new weekend layer, Chainlink is moving toward full-time coverage as tokenized equities and other real-world assets continue to expand onchain.
Hyperliquid’s HYPE has climbed 17.4% to $93.74 on Oct. 29 as NYSE owner Intercontinental Exchange has announced plans for regulated U.S. perpetual futures markets using the blockchain’s infrastructure. CoinGecko showed the token trading within a 24-hour range of $78.11 to…
Polygon Labs decided to bring its Open Money Stack to Solana.
Businesses get bank funding, wallets, cross-chain transfers and global payouts through one integration.
Kira, a fintech focused on cross-border dollar payments, is among the first adopters.
Solana says it has handled over $5T in stablecoin volume this year, while Polygon Chain has passed $3T cumulatively.
Polygon Extends Open Money Stack to Solana
Polygon Labs is making a clear play for the payments market. The firm has rolled out its Open Money Stack on Solana, giving companies a single entry point for bank deposits, embedded wallets, cross-network transfers, and payouts.
Developers don’t need to rebuild anything on Solana. This means that teams can adopt the whole package or plug in only the pieces they’re missing. Polygon Foundation CEO Sandeep Nailwal framed it as a way for businesses to stay on the chain their customers prefer while Polygon manages the movement of money around it.
The platform links bank transfers, cards, cash services, and crypto funding to apps running on Solana. Users receive accounts and built-in wallets, so they can hold and send digital assets without juggling a separate crypto app.
From there, some of the funds are being routed between Solana, Polygon, Ethereum, TRON and several EVM-compatible chains. Polygon handles conversions, routing, and execution on the backend.
Two examples stand out. A remittance company could pull dollars from a customer’s bank, send USDC over Solana and trigger a local bank payout abroad. A marketplace could accept stablecoins and pay sellers in crypto or local currency. In both cases, users never touch a bridge.
Kira’s use case is the is most concrete. The company serves fintechs, OTC desks and import brokers who regularly pay overseas suppliers. It already moves stablecoins on Solana, and CEO Edrizio De La Cruz said the missing piece was getting those funds into clients’ dollar bank accounts. Polygon’s infrastructure fills that gap. Kira joins Tazapay, Mesh and Toku, which Polygon named as early customers after the Coinme deal closed.
Stablecoin Volume Sets the Stage
Solana Foundation product chief Vibhu Norby said the network has processed more than $5T in stablecoin volume in 2026, and he described Polygon’s stack as another route for businesses to reach banking and payout networks.
Solana has been building its own institutional payments team too. In September it hired former Polygon executive Jamal Raees as general manager of payments. Meanwhile, Polygon says its own chain has cleared over $3T in cumulative stablecoin transfers.
This might be a sign that payments infrastructure is becoming chain-agnostic, with the competition shifting from which network wins to who controls the bridge between blockchains and bank accounts
TL;DR: The Depository Trust Company, part of DTCC, launched its tokenization service on October 28, moving a particularly important part of institutional blockchain discussion from experimentation toward live market infrastructure. For digital-asset markets, the launch is a reminder that tokenization may expand blockchain activity without immediately translating into buying pressure for a particular cryptocurrency.
The Depository Trust Company, part of DTCC, launched its tokenization service on October 28, moving a particularly important part of institutional blockchain discussion from experimentation toward live market infrastructure. The company says its system creates tokenized representations of securities already held in DTC custody rather than issuing unbacked substitutes. The launch initially integrates the Canton Network and DTCC’s private Besu environment, while further network connections are planned for 2027. This distinction between an existing security and a digital representation of it matters: legal entitlement and the depository’s established controls remain central to the design.
The event and the market response
DTCC describes the service as a way for authorized participants to move eligible assets between traditional and tokenized environments, with potential uses in collateral mobility, capital efficiency and access to liquidity. The important innovation is not that a stock can appear in a wallet, but that institutions may be able to reuse the same underlying holding in different approved workflows without relying on disconnected records. The company also names a broad ecosystem of technology and market participants working on connectivity, including custody, trading, wallet and application specialists. Launching the service does not mean every asset can immediately circulate everywhere.
Why the development matters to the crypto market
For digital-asset markets, the launch is a reminder that tokenization may expand blockchain activity without immediately translating into buying pressure for a particular cryptocurrency. Canton and a private Besu deployment serve regulated workflows; neither should be confused with public token speculation. Still, dependable post-trade plumbing could create demand for adjacent services such as onchain cash, identity checks and compliant collateral management. The most interesting question is whether institutions can complete an entire trade lifecycle across the new rails, rather than only hold a mirrored security position.
The distinction between a blockchain record and the economic rights behind it is crucial for anyone evaluating this news. Digital tokens may move quickly, but title, custody, investor eligibility and redemption remain governed by legal agreements and regulated entities. A new integration should therefore be judged by the processes it can complete end to end, not simply by the number of assets it can represent. Traders also need to resist treating institutional enthusiasm as an automatic bullish signal for a native cryptocurrency: commercial adoption and token pricing can diverge for long periods.
What the headline does not establish
Operational details will determine the size of the change. Eligible instruments, transfer restrictions, corporate actions, investor protections, and the availability of a cash settlement leg all shape whether tokenization becomes a practical alternative to established processes. DTCC has presented a staged, interoperable model, not a promise that market hours or regulatory requirements have disappeared. Investors should also distinguish a network going live from widespread transaction volume: institutional access, integrations and real usage can rise at different speeds. Tracking the conversion process and participating firms will be more informative than counting announcements alone.
What to watch next
The next evidence to look for is the breadth of assets actually used, the pace of participant onboarding, and examples of completed collateral or settlement transactions. Any expansion into additional chains in 2027 should be assessed against operational reliability and regulatory clarity, not treated as automatic adoption.
Arkham now puts full wallet history, cross-chain tracing and risk scores behind a paid Enterprise tier. I followed a real $26 million theft with two Bitquery tools, then lined up five more options.
Arkham’s free plan now shows only the last 100 transactions of any wallet. To see the rest, you need Arkham Enterprise. That paid tier also holds risk scores, case files and tracing from one chain to another. Arkham launched it on 20 October 2026, and its announcement lists no price.
A busy wallet can make 100 transactions in an afternoon. So if you chase stolen funds or check wallets for a compliance team, the free plan now stops early. If that is you, you need an Arkham Intelligence alternative, at least for part of the work.
I wanted a fair test, so I took one real theft and followed it to the end. On 8 January 2026, an attacker took 8,535 ETH from Truebit, an Ethereum project with its own token. That was about $26.4 million at the time. Within 53 hours, all of it had gone into Tornado Cash, a mixer that pools many people’s coins so the trail breaks.
I ran that trail through both Bitquery tools myself. For the other five, I say what each does best and where it stops.
The short version
Bitquery MoneyFlow (lite.bitquery.io): a free, Arkham-style flow chart in your browser. Paste a wallet, pick one of 17 chains, and follow the money one step at a time.
Bitquery MCP: for people who work in Claude, ChatGPT or Cursor. Ask in plain English, and the AI pulls live transfers and labels from 19 chains, plus risk scores for Ethereum, Bitcoin and TRON.
Nansen: for trading research and “smart money” wallets.
Chainalysis Reactor and TRM Labs: what police and large compliance teams buy. Prices come by quote.
Dune: for people who write SQL and want dashboards.
Etherscan: free, and fine for checking one wallet or one transfer at a time.
Why people look for an Arkham Intelligence alternative
Arkham Intelligence is a blockchain analytics platform, and it built its name on labels. A label is a name attached to a wallet address, such as “Binance hot wallet”. Arkham says it holds 3.9 billion “attributions”, its word for these labels. Those labels stay free, along with its graph tool, called Visualizer, and its block explorer.
the full transaction history of a wallet, with filters (free users see the 100 most recent transactions)
Tracer 2.0, which follows money across bridges, the services that move coins between chains
the counterparties panel, which shows who a wallet deals with most
risk scores and case management
creating new custom labels
Arkham does give free Enterprise access to some independent investigators and public-interest groups through a grant program. Everyone else has to ask for a price.
The API is gated too, with one exception. You apply through a form, and once Arkham approves you, paid plans start at $100, billed in monthly credits. Arkham also hosts an MCP server, so Claude, Cursor or Codex can query its data, but it needs that API plan or a trial. The exception is for AI agents: about 90 read endpoints sold one call at a time, at $0.20 per credit in USDC, with no account.
I get why Arkham moved full history behind a paywall. Serving full history for every wallet costs money. Still, Arkham keeps one big edge. If your main question is who owns a wallet, its free labels are hard to beat, and nothing on this list replaces them one for one. The tools below compete on history, access and price instead.
The test case: the $26 million Truebit hack
Truebit sold its TRU token through its own sale program on Ethereum, written in 2021. A math bug in that old code made the price of new TRU come out as zero. The attacker minted TRU for free, sold it back for ETH, and repeated the trick several times in one transaction. Security firm SlowMist put the loss at $26.44 million.
Here is the trail, as the two Bitquery tools showed it:
8 January, 16:02 UTC. 8,535 ETH lands in the attacker’s wallet, 0x6C8E鈥�2b50 (transaction).
Same day. The wallet splits the money: 4,267 ETH to one new wallet, 4,001 ETH to another. A third payment of 268 ETH follows on 10 January.
8 to 10 January. The 4,267 ETH pile hops through three more new wallets. The 4,001 ETH pile makes one hop.
10 January. Two final wallets feed Tornado Cash in round amounts of 100, 10, 1 and 0.1 ETH. By 20:52 UTC, 8,535 ETH has gone in, the same amount that was stolen.
Any tracing tool should answer three questions about a trail like this. Where did the money come from? How did it split? Where did it end up?
1. Bitquery MoneyFlow: visual crypto tracing in your browser
MoneyFlow is Bitquery’s browser tool for tracing money between wallets. It lives at lite.bitquery.io, and it is free: you only need to sign in with a Bitquery account.
Starting a trace takes four steps:
Paste an address.
Pick the chain. On 29 October the menu listed 17: Bitcoin, Ethereum, BNB Smart Chain, Polygon, Arbitrum, Base, Optimism, TRON, XRP Ledger, Cardano, Litecoin, Dogecoin, Dash, Algorand, Filecoin, Arc and Robinhood Chain.
Pick the coin or token. MoneyFlow lists every currency the wallet has touched, with the date it last moved.
Set a date range if you want one, then press Create MoneyFlow.
The result is a flow chart. Money coming in sits on the left, money going out sits on the right, and the width of each band shows the amount. For the Truebit wallet, one green band of 8,535 ETH comes in and splits into red bands of 4,267, 4,001 and 268 ETH.
Trace Out adds the next step of the trail, and Trace In walks back toward the source. Each step saves a new version of the trace, so you can go back if a step gets messy.
The table under the chart shows Bitquery’s labels next to each address. Both wallets that took the big piles carry the tag hacker-truebit-hacker. Exchange wallets get tagged too. When I traced the Bybit hacker’s wallet from February 2025 the same way, the money came from a Bybit wallet tagged bybit-proof-of-reserves.
The chart also showed something I did not expect. A fan of tiny payments, each worth less than $1, came into the attacker’s wallet from look-alike addresses. One look-alike copies the first and last four characters of a wallet the attacker used, so both read 0x3b58鈥�862a in short form. The trick is called address poisoning. Scammers hope you copy the fake address from your history next time, and here they aimed it at the thief. A threshold box above the chart hides payments below any dollar amount you choose.
Two more buttons help when you need to share the work. Generate report turns the trace into a table of every transfer, with full hashes, which you can download as a CSV file. Get API opens the query behind the chart in Bitquery’s GraphQL IDE, so a developer can run it again.
Where it falls short. Solana is not in the chain menu yet. Each trace follows one currency, so if a thief swaps ETH for USDT, you start a second trace. And after a few steps the chart can turn into loops when money flows back into wallets already on it. In the Truebit case, the third step got hard to read, and the table was clearer.
2. Bitquery MCP: ask your AI assistant to follow the money
MCP, short for Model Context Protocol, is a standard way to plug outside tools into an AI assistant. Bitquery MCP plugs live blockchain data into Claude, ChatGPT, Cursor, VS Code and OpenAI Codex.
Setup is short. Add https://mcp.bitquery.io as a custom connector in your assistant, then sign in with your Bitquery account. There is no API key to paste.
You then get 314 tools. They trace transfers on 19 chains, including Solana, Bitcoin, Ethereum, TRON, the XRP Ledger and Stellar. They also cover DEX trades and prices on 10 chains. Guided prompts handle the common jobs: money_flow follows funds until they reach an exchange or a mixer, and risk_screen returns a LOW, MEDIUM or HIGH verdict with evidence.
I gave Claude the Truebit attacker’s wallet and asked where the ETH ended up. I also asked it to name every wallet on the way and score the last ones for risk. It pulled the transfers hop by hop, looked up the labels and ran a risk check on each final wallet.
The answer named two exit wallets. The first, 0x7720鈥59d, got 4,267 ETH after three more hops and sent 4,266.9 ETH to Tornado Cash on 10 January. The second, 0xd841鈥135, got the 4,001 ETH pile plus the 268 ETH payment and sent 4,268.5 ETH to Tornado Cash the same evening. Both scored 100 out of 100 for risk, the top of the scale, mainly because they paid a mixer. The risk check also flagged look-alike poisoning addresses next to both.
MoneyFlow reached the same Tornado Cash address three steps out from the attacker. The MCP got there from one question. Arkham has a hosted connector too, so the real difference is access. Arkham’s needs an approved API plan or trial, while Bitquery’s trial is self-serve and needs no card.
The product page listed three plans on 29 October 2026. The free trial runs 7 days with 100 credits, and it needs no card. Trading MCP costs $19 per month and covers trading data only, with 32 tools and no tracing. AI Investigation MCP, the plan with tracing, costs $149 per month, or $100 per month billed yearly, and includes all 314 tools.
Where it falls short. On Ethereum the risk check looks one step out from a wallet; on TRON it can look several steps. An AI assistant can also misread a result, so open the transaction hashes it cites before you rely on them. And like MoneyFlow, it follows one chain at a time, so you hop a bridge yourself.
Arkham vs Bitquery at a glance
In words: Arkham’s free plan shows the last 100 transactions per wallet, while MoneyFlow uses whatever date range you set and the MCP pages through the full history. Arkham’s Visualizer stays free, and MoneyFlow draws a flow chart too; the MCP answers in text.
Arkham Enterprise follows money across bridges for you. MoneyFlow and the MCP work one chain at a time. Risk scores come with Arkham Enterprise and with Bitquery MCP, not with MoneyFlow.
Price works differently on each side. MoneyFlow is free with a Bitquery account. Arkham Enterprise lists no price. Its API starts at $100 after approval, or $0.20 per credit pay as you go. Bitquery MCP is self-serve, with a free trial and then $149 per month for tracing.
5 more Arkham alternatives worth knowing
3. Chainalysis Reactor
Best for police, prosecutors and large exchanges. Reactor is Chainalysis’s case graph, and law enforcement uses it widely. There is no public price and no self-serve trial. If you work alone or on a small budget, it is likely out of reach.
4. TRM Labs
Best for compliance teams and government buyers. TRM sells its Forensics tool for tracing funds across chains, next to its wallet screening tools. Most of it is sold by quote, mainly to large firms.
5. Dune
Best for analysts who write SQL. Dune lets you query blockchain data and build dashboards, and it has a free tier and its own MCP server. There is no ready-made tracing screen, so you write the queries yourself or let its MCP server write them.
6. Etherscan
Best for checking one transaction or one wallet for free. Etherscan shows name tags on well known addresses, and it tags the Truebit attacker’s wallet “Truebit Exploiter 1”. There is no flow chart, so tracing a trail across many hops means a lot of tabs.
7. Nansen
Best for trading research. Nansen labels wallets and marks the ones with a strong record as “smart money”. You can then watch what they buy and sell. There is a free tier and a paid Pro plan, plus an API, an MCP server and a command-line tool. Its tools center on trading signals, so it is a weaker fit if you need to build a case file.
Other Bitquery products for investigators
Bitquery sells three more things for this kind of work:
Coinpath: the money-flow data behind MoneyFlow, sold to companies with full history and bulk export.
Crypto investigation service: if you were robbed and would rather hand the work to someone, Bitquery’s team traces the funds. Its page says the first assessment is free.
Ethereum datasets: the full history of the chain as files, for teams that want to run their own analysis.
How to choose an Arkham alternative
You want Arkham’s look without paying for Enterprise: Bitquery MoneyFlow, which is free.
You already work in Claude or ChatGPT: Bitquery MCP.
You trade and want smart-money signals: Nansen.
You work for police or a regulated firm with a budget: Chainalysis Reactor or TRM Labs.
You write SQL: Dune.
You only need to check one transfer: Etherscan.
FAQ
Is there a free alternative to Arkham Intelligence?
Yes. Bitquery MoneyFlow is free with a Bitquery account and traces a wallet over any dates you pick. Etherscan is free for looking up one wallet or transaction at a time, and Dune has a free tier. Bitquery MCP has a 7-day free trial with 100 credits and no card. Arkham itself still has a free plan, but it shows only the last 100 transactions per wallet.
What is the best Arkham alternative for tracing stolen crypto?
For a visual trail, Bitquery MoneyFlow; for asking questions in plain English, Bitquery MCP. For court work with a large budget, Chainalysis Reactor or TRM Labs. I work at Bitquery, so weigh my pick with that in mind.
Does Arkham have an API?
Yes. You apply through Arkham’s API form, and once Arkham approves you, plans start at $100, billed in monthly credits. Some applicants get trial access first. Arkham also hosts an MCP server for AI assistants, and AI agents can pay per call at $0.20 per credit in USDC.
Can AI trace crypto transactions?
Yes, if the assistant is connected to live blockchain data. With Bitquery MCP, Claude followed the Truebit money to Tornado Cash and scored both exit wallets 100 out of 100 for risk. Check the transaction hashes it cites before you act on them.
Can you trace crypto after it goes into Tornado Cash?
Not directly. A mixer pools many people’s deposits, so the link between a deposit and a withdrawal breaks. Investigators match the timing and size of later withdrawals, which is slow and gives odds, not proof.
Try it yourself
Start a trace at lite.bitquery.io, or connect Bitquery MCP to your AI assistant and ask it to follow a wallet. If you want the raw history instead, Bitquery sells the Ethereum dataset as files.
Solana co-founder Anatoly Yakovenko questions projects outside the main blockchain as BULK defends its decision to expand trading across multiple networks.
Sony Group has launched a global blockchain incubation program to support startups and creators building new entertainment services on its Soneium network. According to an October 29 announcement, the initiative, called the Sony Onchain Entertainment Incubation Program, will provide selected…
Google is preparing to expand its crypto security operations with a new Multi-Party Computation (MPC) service targeting institutional digital asset custody. The move comes as a fresh vulnerability in Fireblocks’ MPC library highlights the risks buried inside crypto key-management systems.
Google MPC is reportedly in private preview, with major financial institutions testing the service. The technology is also being used to secure digital assets on Ethereum and Solana, with commercial availability expected in early 2027.
The timing puts institutional crypto security under renewed scrutiny. On October 26, CERT/CC disclosed a vulnerability in Fireblocks’ MPC library that could weaken protections separating cryptographic key shares.
CERT/CC’s Oct 26 advisory describes a hardened-derivation flaw in Fireblocks’ mpc-lib, CVE-2026-90975. A compromised descendant signer share plus its chain code can expose that party’s ancestor shares. This does not independently recover a full spendable key; MPC threshold…
MPC allows multiple parties to participate in transaction signing without assembling a complete private key in one place. Instead, each participant holds a separate key share, and the parties collaborate to authorize transactions.
This design reduces the risk associated with a single compromised device or insider. However, MPC does not eliminate vulnerabilities in the software handling those shares.
Google Cloud has previously supported institutional MPC deployments through Confidential Space, which uses confidential computing and hardware-backed attestation. These safeguards help verify sensitive workloads and restrict access to protected data, including during blockchain transaction signing.
The reported Google MPC service would take the company further into dedicated institutional crypto security. Its appeal could lie in combining cloud infrastructure with cryptographic controls designed for organizations managing substantial digital asset holdings.
Now, institutions will still need to assess implementation details, transaction approval policies, and recovery procedures. MPC itself is a cryptographic technique, not a guarantee that every component of a custody system is secure.
Fireblocks MPC Vulnerability and Key Security Risks
CERT/CC published vulnerability VU#701544 on October 26, identifying a flaw in Fireblocks’ mpc-lib library. The issue affects its implementation of BIP32 hardened key derivation when a required private parent key is missing.
According to the advisory, the library can substitute a zero-filled buffer instead of rejecting the operation. If an attacker also obtains a compromised descendant signer share and its associated chain code, the attacker may recover ancestor shares within that party’s key hierarchy.
The flaw does not expose a complete, spendable private key. Instead, it weakens an additional protection designed to limit how far a compromised share can expose related key material.
CERT/CC said no vendor fix was available when its advisory was published. It recommended keeping chain codes confidential and avoiding reliance on hardened derivation to isolate signer shares until the implementation is corrected.
The incident illustrates why Google MPC security will need to be evaluated at the implementation level. Distributing private keys is one layer of protection, but derivation logic, access controls, and transaction approval mechanisms also matter.
Hidden Economics of Asset Tokenization: What It Actually Costs to Bring $100 Million in Assets On-Chain
Tokenizing $100 million in assets is a technical milestone. Making the infrastructure commercially viable is an entirely different challenge.
Imagine an investment firm preparing to tokenize $100 million in real estate, private credit, or other financial assets.
The business case looks promising. Blockchain-based ownership records could simplify transfers, fractional ownership could expand investor participation, and automated processes could reduce administrative work.
But the firm faces a question that rarely appears in tokenization market forecasts:
How much money must the business spend before its first token generates meaningful revenue?
The answer extends far beyond smart contract development.
Legal structuring, asset verification, investor onboarding, custody arrangements, compliance systems, and ongoing administration all contribute to the economics of tokenization.
And these costs do not necessarily decline simply because assets are represented digitally.
According to McKinsey’s research on tokenized financial assets, the market could reach approximately $2 trillion by 2030, excluding cryptocurrencies and stablecoins. Its optimistic scenario approaches $4 trillion.
Yet the same research highlights an important obstacle: implementing tokenization infrastructure can require substantial investment before the anticipated efficiencies become commercially meaningful.
For businesses entering this market, the central question is no longer whether assets can be tokenized.
It is whether the financial benefits justify the infrastructure required to tokenize them.
$100 Million in Tokenized Assets Is Not $100 Million in Revenue
One of the most important distinctions in tokenization economics is the difference between asset value and business income.
Consider a platform that successfully issues digital tokens representing $100 million in underlying assets.
That figure might represent assets issued, assets administered, or assets currently held through the platform.
It does not represent revenue earned by the platform operator.
Revenue depends on the commercial arrangement.
A platform might charge asset issuers for token creation, collect recurring administration fees, license infrastructure to institutions, or earn transaction fees where legally permitted.
For example, a hypothetical 0.50% annual administration fee on $100 million in fee-bearing assets would generate $500,000 in gross annual revenue.
That sounds attractive until the operating costs enter the calculation.
The platform may still need to pay for regulatory compliance, custody services, infrastructure maintenance, security assessments, investor support, and asset servicing.
Moreover, a platform might tokenize $100 million over several years without ever maintaining $100 million in active fee-bearing assets.
Tokenized asset value measures the scale of assets represented. Revenue measures the commercial value the platform captures.
Confusing the two can lead businesses to overestimate their potential returns before development begins.
The Six Expenses Behind a $100 Million Tokenization Project
To understand the economics, consider a hypothetical financial services company launching a custom platform to support $100 million in tokenized assets.
Assume the company already has access to suitable assets and intends to serve professional or otherwise eligible investors.
The following model illustrates one possible initial budget.
The important observation is not the $500,000 total.
It is how the money is distributed.
1. Platform Development: $180,000
A production-ready tokenization platform requires more than a mechanism for creating blockchain tokens.
Depending on the business model, it may need investor dashboards, asset issuance workflows, ownership records, subscription management, payment integrations, reporting tools, and administrative controls.
For companies evaluating Asset Tokenization Platform Development, the critical budgeting decision is determining which capabilities must be developed internally and which can be integrated through existing infrastructure providers.
Custom development offers greater control over workflows and future functionality, but it also creates ongoing maintenance responsibilities.
A lower initial software budget is not necessarily cheaper if the platform later requires expensive architectural changes.
2. Legal Structuring and Regulatory Preparation: $120,000
Representing an asset on a blockchain does not automatically establish legally enforceable ownership.
The business must determine what the token represents.
Does it convey direct ownership, an interest in a legal entity, a debt claim, or contractual rights against an issuer?
Each structure can introduce different legal, disclosure, investor eligibility, and transfer requirements.
Depending on the jurisdiction and offering structure, businesses may need legal opinions, offering documentation, regulatory advice, entity formation, and agreements with regulated intermediaries.
Some structures may also require licenses or authorization before operations begin.
These obligations cannot be eliminated through software automation.
3. Smart Contract Development and Security Audits: $65,000
Smart contracts can automate token issuance, transfers, restrictions, and selected asset-related operations.
But automation introduces another category of financial risk.
A poorly designed contract could allow unauthorized transfers, incorrectly enforce ownership restrictions, or create vulnerabilities affecting investor assets.
Security testing and independent audits therefore deserve their own budget.
Audit costs also depend on the number of contracts, their complexity, the maturity of the underlying code, and the extent of remediation required.
Importantly, a completed audit does not guarantee that a system is free from vulnerabilities.
4. Asset Verification and Onboarding: $45,000
Before tokenization, the underlying asset must be verified.
For real estate, this may involve ownership documentation, title review, valuation, and property-related due diligence.
Private credit assets may require loan documentation, borrower information, collateral assessment, and servicing arrangements.
Tokenization does not remove the need to establish that an asset exists, belongs to the relevant party, and supports the rights being offered.
The blockchain records the digital representation.
It does not independently verify every claim made about the underlying asset.
5. Custody and Security Infrastructure: $40,000
Businesses must decide how digital assets and signing credentials will be controlled.
Possible arrangements include institutional custody providers, multisignature authorization systems, and multiparty computation infrastructure.
The appropriate approach depends on legal obligations, the operating model, and the parties responsible for safeguarding assets.
Integrating custody also introduces expenses related to access controls, transaction approvals, key recovery procedures, and operational monitoring.
6. Testing and Operational Readiness: $50,000
A tokenization platform can function successfully in a demonstration environment while remaining unprepared for real investors.
Production testing should examine investor onboarding, transaction failures, restricted transfers, corporate actions, reconciliation, reporting, and recovery procedures.
These workflows become especially important when blockchain records must remain consistent with legally authoritative off-chain records.
Launching the software is only one part of launching the business.
The Expense That Changes Everything: Running the Platform After Launch
Initial development expenditure receives considerable attention.
Recurring operational expenditure deserves just as much.
Consider an illustrative annual operating budget for the same platform.
Under these assumptions, the business would commit approximately $750,000 across its initial investment and first year of operations.
This excludes financing costs, taxes, asset acquisition costs, major unforeseen expenses, and other items that may apply to a particular business.
The first-year cash requirement could therefore be materially higher.
A company focusing exclusively on development costs may underestimate the capital needed to reach sustainable operations.
This problem is particularly significant when a platform must maintain both blockchain-based and conventional financial records.
In its analysis of tokenization adoption, McKinsey identifies the expense of operating traditional and digital processes simultaneously as a barrier to achieving near-term economic benefits.
Tokenization can create efficiency.
But during implementation, it can also temporarily increase operational complexity.
The Break-Even Calculation Most Tokenization Business Plans Need
Now consider the commercial consequences of the financial model.
The platform has:
$500,000 in initial investment.
$250,000 in annual operating expenses.
$100 million in fee-bearing assets.
A hypothetical 0.50% annual administration fee.
Its annual gross revenue would be:
$100 million × 0.50% = $500,000
After deducting $250,000 in annual operating expenses, the business would retain $250,000 before taxes, financing costs, and other excluded expenses.
If the full $100 million remains fee-bearing, all revenue is collected, and annual expenses remain constant, recovering the $500,000 initial investment would take approximately two years.
But consider what happens when the assumptions change.
Under this simplified model, the platform needs approximately $50 million in fee-bearing assets merely to cover its assumed annual operating expenses.
It must generate additional surplus to recover development costs.
And that calculation assumes every dollar of the relevant asset base generates the same fee.
In reality, fee discounts, onboarding delays, client departures, and changing asset values could materially affect revenue.
The financial viability of a tokenization platform depends less on how many tokens it can issue than on how consistently it can generate revenue from the assets and services it supports.
Where Tokenization Can Actually Produce Financial Savings
Tokenization is frequently associated with lower transaction costs and faster settlement.
Those benefits are possible, but they are not automatic.
The potential economic advantage comes from reducing duplicated processes and coordinating transactions more efficiently.
For businesses, three areas deserve particular attention.
Administrative automation: Automated ownership updates, distribution calculations, and transfer restrictions may reduce manual processing requirements.
Reconciliation efficiency: Shared transaction records may reduce the need for separate parties to repeatedly compare inconsistent information.
Settlement coordination: Where appropriate payment and asset infrastructure exists, programmable settlement arrangements may reduce delays and counterparty exposure.
However, businesses should measure these benefits against their existing processes.
If a company already operates an efficient, low-cost administrative system, replacing it with blockchain infrastructure may not immediately generate meaningful savings.
Likewise, faster on-chain transfers do not automatically resolve legal settlement requirements or eliminate traditional asset-servicing responsibilities.
The relevant metric is not the theoretical speed of the blockchain.
It is the reduction in the total cost of completing a legally valid financial transaction.
The $100 Million Question: Build, License, or Outsource?
Once the economic model is established, businesses face another decision.
Should they develop their own tokenization infrastructure, license an existing platform, or outsource selected operations?
Each approach changes the relationship between upfront expenditure, recurring costs, and operational control.
A company planning a limited issuance may find that custom infrastructure creates unnecessary financial exposure.
An institution expecting repeated issuances across several asset classes may place greater value on controlling its own technology and integrations.
It is the total cost of ownership over three to five years, including integration, compliance, maintenance, vendor charges, and the financial consequences of changing providers.
That calculation can reveal whether an initially inexpensive solution remains economical as the business expands.
What the Market Data Reveals — and What It Doesn’t
The tokenized asset market is growing, but aggregate market figures require careful interpretation.
As of October 11, 2026, RWA.xyz’s platform dashboard reported approximately $39.22 billion in distributed asset value and $357.50 billion in represented asset value.
These figures describe different categories of asset representation and should not be combined as though they measure the same thing.
They also do not reveal how much revenue tokenization infrastructure providers earn.
Nor do they establish that every tokenized asset has an active secondary market.
A tokenization platform can administer substantial asset value while generating relatively little transaction activity.
That matters because some business models depend on recurring administration fees, while others rely more heavily on issuance volume or trading-related revenue.
The same $100 million asset portfolio could therefore produce very different financial outcomes depending on how the platform earns money.
Businesses should evaluate market growth alongside customer demand, asset turnover, fee structures, and operating expenses.
Market size can demonstrate opportunity.
It cannot establish the profitability of an individual business.
Five Questions Worth Answering Before Committing Capital
The financial analysis leads to five questions that deserve answers before a tokenization project receives its development budget.
1. What specific cost or market limitation will tokenization solve?
A credible business case should identify measurable improvements rather than relying on blockchain adoption as an objective.
2. How much of the underlying asset value will actually generate revenue?
Total issued asset value and fee-bearing assets may differ substantially.
3. Which operational responsibilities will remain outside the blockchain?
Legal administration, custody, reporting, investor verification, and asset servicing may continue to require specialized providers.
4. What happens if adoption reaches only 25% of the original forecast?
A viable financial model should survive slower onboarding, lower issuance volumes, and higher operating expenses.
5. At what scale does the platform become economically sustainable?
This requires calculating the minimum revenue needed to cover recurring costs and eventually recover the initial investment.
These questions do not guarantee commercial success.
They help prevent a technically successful project from becoming an economically unsustainable one.
The Real Economics Begin After the First Token Is Issued
Bringing $100 million in assets on-chain can be an important technological achievement.
But it does not automatically create a profitable platform, eliminate traditional financial obligations, or produce liquid markets.
The financial outcome depends on how effectively the business converts its infrastructure investment into recurring revenue, operational savings, or measurable strategic advantages.
Under the illustrative model explored here, a $500,000 initial investment and $250,000 in annual operating expenses create a meaningful financial commitment before the platform achieves scale.
Different assumptions could produce dramatically different results.
That is precisely why tokenization projects should begin with financial modeling rather than technology selection.
The businesses most likely to benefit from tokenization will not necessarily be those that issue the greatest number of tokens. They will be those that understand the economics of issuing, managing, and servicing those tokens over time.
The most important question is not simply what it costs to put $100 million on-chain.
It is what the business must earn — or save — to make that investment worthwhile.
Turning Tokenization Economics Into Production-Ready Infrastructure
Understanding the economics of asset tokenization is only the first step. Translating those financial assumptions into a secure, scalable platform requires an architecture that supports the business model from issuance through ongoing asset administration.
Softean develops custom RWA asset tokenization platforms for businesses, asset managers, and financial institutions seeking to digitize real-world and financial assets. Our development capabilities span token issuance, investor onboarding, smart contract integration, compliance-enabled workflows, ownership management, custody connectivity, and asset administration.
Rather than approaching tokenization as a standalone blockchain implementation, we focus on building infrastructure around each client’s asset structure, operational requirements, and long-term platform objectives.
Whether a business is preparing its first tokenized offering or planning a multi-asset tokenization ecosystem, Softean helps translate its requirements into a practical development roadmap.
Planning an asset tokenization platform? Explore Softean’s development capabilities and discuss the infrastructure your business needs to bring tokenized assets to market.
A six-step method that starts at the contract, not the dashboard.
Four deductions separate raw contract supply from the circulating supply figure you can actually defend.
Pick a large stablecoin. Open three data sites. You will get three different circulating supply numbers.
None of them is lying. They are answering three different questions.
And the gap is not cosmetic. In June 2026, one widely used aggregator reported roughly $371 million more USDS than the Ethereum mainnet contract did. No hack. No stealth mint. Escrowed supply counted twice.
If you hold a stablecoin, lend against one, or carry one on a balance sheet, you need a figure you can defend in a risk meeting. Here is the six-step method.
Three published supply figures for the same stablecoin, read at the same block on the same day.
Why does the same stablecoin show three different circulating supply numbers?
Three structural reasons, and not one of them involves anybody being dishonest.
Different starting point. Some sources read totalSupply() straight off the token contract. Others rebuild supply by summing mint and burn events. Onchain data schemas now carry an explicit flag for which of the two is authoritative, row by row, because the two disagree often enough to matter.
Different exclusions. CoinGecko deducts locked addresses that project teams report to it (published methodology). Allium strips four separate categories out of raw supply before calling anything circulating.
Different scope. One token, or the whole family? USDS alone sat at $6.81B on 26 October 2026. Sky Ecosystem reported $11.48B of stablecoin supply the next day, because that figure counts USDS and DAI together as protocol liabilities.
Same dollar. Three honest answers.
Circulating supply is not a fact you look up. It is a definition you choose, then measure.
Step 1. Read the contract before you read the dashboard
Every real audit starts with one call: totalSupply() on the issuing contract, at a named block.
Not a screenshot. A block height.
Yearn’s risk team did exactly that to USDS on 9 September 2026 at block 25939320. Mainnet totalSupply() came back at 6,645,559,216, down 15% from their previous reading.
They also pulled the protocol’s own internal debt figure, so the token number could be checked against the issuer’s books rather than against another website. The full working is public.
That is the standard worth copying. Two independent reads, same block, both published.
Step 2. Subtract the supply that is not actually circulating
Raw total supply overstates circulation almost every time. Four buckets come out:
Pre-minted and unissued. Tokens the issuer created but has not released against backing.
Bridge-locked. Supply sitting in a source-chain escrow while a mirrored token trades somewhere else.
Stablecoin-backed. Supply locked only to mint another tracked stablecoin.
Permanently inaccessible. Burn addresses and dead contracts.
The bridge bucket is where most errors live. In that same September reassessment, native-escrow USDS fell from about $448M to $102M, escrowed sUSDS from about $812M to $343M, and LayerZero-locked USDS from roughly $48.7M to $6.67M. Miss those and a cross-chain total quietly counts real money twice.
Bridge escrow and locked balances move fast, and a supply audit has to re-read them every time.
Step 3. Do not count the yield-bearing wrapper twice
This one catches careful people.
sUSDS is not extra supply. It is a claim on USDS that has been supplied to the Sky Savings Rate module. One dollar of USDS wrapped into sUSDS is still one dollar of stablecoin liability, not two.
Count the base token as supply.
Count the wrapper as a holding of the base token.
Never add the two together.
Scale is why this matters. Roughly half of USDS supply sits in sUSDS, and the Ethereum sUSDS pool showed $4.85B on 26 October 2026. That is a lot of float to misclassify.
Adding the yield-bearing wrapper to the base token counts the same dollars twice.
A yield-bearing wrapper is a claim on supply. It is never new supply.
Step 4. Check what backs the supply, not just how big it is
Supply tells you the size of the liability. It tells you nothing about whether that liability is covered.
So pull the collateral figure next, from the same issuer, on the same day.
On 27 October 2026, Sky Ecosystem published $14.15B in Total Collateral against $11.48B in stablecoin supply.
That is roughly $1.23 of collateral behind every dollar of supply, which is the entire point of an overcollateralized design.
Two surfaces let you check it yourself instead of taking it on trust:
financial.skyeco.com for the balance sheet, Gross and Net Protocol Revenue, Protocol Surplus and Sky Reserves.
info.skyeco.com for the live onchain view of collateral composition, USDS and sUSDS.
Credit agencies have started running the same exercise. Moody’s assigned Sky Protocol a B3 issuer rating with a stable outlook on 7 October 2026, the first rating it has given any stablecoin protocol, after S&P Global affirmed B- on 1 October.
Both flagged reserve depth as the constraint. That is what an outside read of the collateral side looks like, and it is worth more than a logo on a trust page.
Collateral against supply, plus the two outside credit reads, as published in October 2026.
Step 5. Ask whether that supply can actually leave at a dollar
A supply number is only as good as the exit. Three questions:
Is there a direct conversion path with the issuer, or only a market?
What caps sit on that path?
What does using it cost?
Sky Protocol runs Peg Stability Modules, smart contracts that convert supported stablecoins into USDS and back at 1:1 directly with the protocol rather than against another trader, under governance-set caps. Moving between USDS and sUSDS carries no lockup in either direction.
Redemption depth is the part of a supply audit most people skip, and the part every stress event tests.
Step 6. Date the number, or bin it
Stablecoin supply moves daily. A figure without a timestamp is a rumour with decimal places.
Write the audit line in four fields: source, metric, value, block or date.
From 18 January 2027, permitted issuers must publish the monthly composition of their reserves on their own websites by noon on the last day of each month, and file weekly confidential reserve reports.
As Forbes noted, an accurate weekly reserve figure demands daily reconciliation between tokens outstanding onchain and reserves held at the custodian.
Monthly PDFs are becoming weekly reconciliation. Protocols that already publish live will barely feel it.
What does a finished circulating supply audit look like on USDS?
Six lines, dated 26 to 27 October 2026, each checkable in under ten minutes:
Mainnet token supply: $6.81B USDS, third largest dollar stablecoin.
Protocol family supply: $11.48B, USDS and DAI together.
Total Collateral: $14.15B, around $1.23 per dollar of supply.
Wrapper: sUSDS, roughly half the USDS float, excluded from the supply line.
Exit path: Peg Stability Modules at 1:1, governance-capped.
Outside read: rated by both Moody’s and S&P Global, so far the only stablecoin protocol with both.
A defensible number, with the working shown.
Why the Sky Savings Rate belongs in a supply audit
Here is the part most supply write-ups leave out.
Supply that pays nothing is a static liability. Supply that pays has to be funded, and that funding has to come from somewhere real.
The Sky Savings Rate is a variable rate set by Sky Governance and accessed by holding sUSDS.
It is funded from revenue Sky Protocol accrues as the Sky Agent Network, independent allocators including Spark, Grove, Osero, Keel and Obex, draws USDS liquidity under governance-set risk parameters and deploys it.
So when you audit the supply, audit the engine behind it:
Where does the yield come from?
Who sets the rate, and is the decision public?
Does the revenue appear on a published income statement?
Galaxy appears to have run some version of that test. On 23 September 2026 it added $100 million of sUSDS to its corporate treasury and approved sUSDS as eligible collateral across its institutional trading business.
Audit the supply. Then audit whatever pays it.
The 60-second circulating supply checklist
Run this before you quote any stablecoin supply figure:
Read totalSupply() at a named block.
Subtract pre-minted, bridge-locked, stablecoin-backed and inaccessible balances.
Exclude the yield-bearing wrapper from the supply line.
Pull collateral from the same issuer on the same day.
Confirm the redemption path and its caps.
Write the date next to the number.
Six steps. One figure you can put in front of a risk committee.
So what should circulating supply actually mean?
The stablecoin market sat near $308B in August 2026, below its May peak of $322.4B. That is a lot of dollars measured by methods most holders have never read.
Which leaves the question I actually want argued in the comments.
Does circulating supply mean tokens that exist, tokens that can move, or tokens someone can redeem at par today?
Pick one. Then run the six steps on whatever stablecoin you hold and post the number with its date underneath. I will check mine against yours.
I’d marked them as the likely hidden code. Of the 46 delegates that keep the hash, fewer than half are verified.
The most delegated contract in my EIP-7702 sample ends in these 12 bytes: a164736f6c6343000822000a. Most Solidity contracts built with default settings end in 53. The longer tail is a small CBOR map the compiler appends to the bytecode: an IPFS hash of the contract’s metadata file, the compiler version, and two bytes giving the map’s length. This one has the version and no hash.
On 8 September I pulled every EIP-7702 authorization from a 200-block window on Ethereum mainnet, 1,178 of them, and read the bytecode of the 59 contracts they delegated to. Nine of those authorizations pointed at the zero address, which is how an account undelegates, so 1,169 went to real code. When I went back over the 59 on 11 October, ten had the short tail. I left a note beside them: no metadata hash, so maybe nobody meant the source to be found.
What the 12 bytes still say
Read as CBOR, a1 opens a map with one entry, 64 says a four-byte string follows (solc), and 43 says a three-byte value follows: 00 08 22, which is version 0.8.34. The last two bytes, 00 0a, give the length of everything before them, ten. So the compiler version survives. What’s gone is the hash that would let anyone fetch the exact metadata file, the one that lists every source file’s own hash and the compiler settings. In solc that’s a single setting, metadata.bytecodeHash set to none, and Foundry exposes it as bytecode_hash.
The last bytes of two EIP-7702 delegates. Both record the compiler version; only one carries the metadata hash.
Checking the note
Today I asked Blockscout’s API whether each of the 59 has verified source, and asked Sourcify the same. Nine of the ten stripped contracts are verified on Blockscout. Of the 46 that kept the full hash, 21 are. The other three have no CBOR tail at all, and one of those is verified.
Counting authorizations instead of contracts widens the gap. In that September window, 369 of the 371 authorizations to stripped delegates went to a contract with published source. For the full-hash contracts it was 324 of 774, about 42%.
59 delegate contracts from one 200-block window in September, verification read on 27 October.
The one stripped contract with no source, 0xbaa66503..., drew two authorizations. The second most delegated contract in the whole sample, 0x67b743f3... with 144, carries a full IPFS hash and has no verified source on either service. Neither does 0x912518c2... with 96. Three unverified contracts of 2,140 bytes each carry the same IPFS hash, so they’re one build deployed three times.
Who strips it
The nine verified ones carry six contract names: Uniswap’s CaliburEntry at three addresses, Alchemy’s SemiModularAccount7702 at two, two TokenPocket delegators, UniversalGaslessDelegate, and the most delegated contract of all, with 308 of the window’s authorizations, whose verified source names it Poisoner.
The ten stripped delegates. Blockscout and Sourcify read 27 October; authorizations from the 8 September window.
Calibur’s foundry.toml and the one in Alchemy’s modular-account repository both set bytecode_hash = "none" as the project default. Neither file says why. Five of the ten addresses look mined: two start with eight zeros, one with 0x0000fb7702, one with 0x69007702, and one starts 0x77021100 and ends 0000. The metadata hash changes whenever a comment or a file path changes, even when the compiled code doesn’t, and an address found by searching CREATE2 salts depends on the exact bytecode. Dropping the hash ties the bytecode to the code alone. That’s my reading of the reason, not something either project says.
What Sourcify makes of them
Sourcify answered for eight of the stripped contracts, and all eight came back as match, none as exact_match. Of the full-hash contracts it has, 13 of 17 are exact. Sourcify’s docs say an exact match rests on the metadata hash in the deployed code agreeing with the recompiled one, which is how it proves the source files are byte for byte the ones the author compiled. With no hash in the bytecode there’s nothing for that check to hold on to, so I’d expect every stripped contract to stop at match, whoever wrote it.
What this doesn’t show
The authorization counts come from one 200-block window in September, so they say which delegates were busy then. Verified means Blockscout’s flag and Sourcify’s record as I read them on 27 October. I didn’t check Etherscan, which wants an API key, and a contract could be verified there and nowhere else. I also tried two public IPFS gateways for the hashes on the unverified contracts and both refused the requests, so I can’t say whether any of those metadata files exist somewhere.
Preparing Blockchain Authentication for the Post-Quantum Era: Signature Migration and Compatibility Risks
Blockchain security depends on a fundamental assumption: knowing a public key should not make it computationally feasible to derive its private key. Quantum computing could eventually challenge this assumption, forcing blockchain networks to reconsider how transactions are authenticated, how ownership is verified, and how existing accounts migrate to safer cryptography.
For B2B founders and developers, this is not simply an algorithm upgrade. It is a protocol compatibility, asset recovery, infrastructure, and governance challenge. A successful transition must strengthen cryptographic security without breaking wallets, smart contracts, transaction verification, or access to existing assets.
Why Existing Blockchain Signatures Face a Quantum Risk
Many blockchain networks rely on elliptic-curve cryptography. Ethereum uses the Elliptic Curve Digital Signature Algorithm (ECDSA) over the secp256k1 curve for externally owned accounts (EOAs), while other networks use different signature schemes.
These systems remain secure against known classical attacks when implemented correctly. However, a sufficiently capable, fault-tolerant quantum computer could use Shor’s algorithm to solve the mathematical problem underlying elliptic-curve cryptography.
How quantum computing threatens private keys
In conventional cryptography, deriving a private key from its public key is computationally impractical. Shor’s algorithm could change that by efficiently solving the elliptic-curve discrete logarithm problem on a sufficiently powerful quantum computer.
On Ethereum, an EOA’s address is derived from its public key. Although the public key is not directly displayed in the address, a valid transaction signature allows it to be recovered. Consequently, accounts that have transacted may already have exposed their public keys through transaction history.
This does not mean blockchain wallets can be compromised by quantum computers today. No currently demonstrated quantum computer can break these signatures at the required scale. However, blockchain infrastructure takes considerable time to upgrade, making early preparation important.
Another concern is harvest now, decrypt later. This primarily affects encrypted information rather than ordinary public blockchain transactions, which are already transparent. Nevertheless, organizations using blockchain alongside confidential business data should consider whether long-lived encrypted records could become vulnerable to future quantum attacks.
Post-Quantum Cryptography: What Changes Technically?
Post-quantum cryptography (PQC) uses mathematical problems believed to resist attacks from both classical and quantum computers. The National Institute of Standards and Technology (NIST) finalized two digital-signature standards in August 2024:
ML-DSA (FIPS 204): A lattice-based digital-signature scheme.
SLH-DSA (FIPS 205): A stateless hash-based digital-signature scheme.
Lattice-based schemes rely on the difficulty of solving particular mathematical problems involving structured lattices. Hash-based signatures derive their security from cryptographic hash functions and carefully constructed signing processes.
These standards provide alternatives to vulnerable elliptic-curve signatures, but adoption requires careful engineering.
Why signature size and verification cost matter
Traditional elliptic-curve signatures are relatively compact. Post-quantum signatures can be substantially larger, depending on the algorithm and parameter set. This creates several blockchain-specific challenges:
Transaction size: Larger signatures consume more bandwidth and block space.
Verification cost: Validators must perform different, potentially more expensive cryptographic operations.
Network throughput: Increased transaction sizes and verification workloads can reduce processing capacity.
Wallet compatibility: Existing signing libraries, hardware wallets, and recovery procedures may not support new algorithms.
Smart-contract execution: Contracts designed to verify ECDSA signatures cannot automatically validate ML-DSA or SLH-DSA signatures.
A migration that strengthens cryptography but makes transactions prohibitively expensive is not a successful production migration.
Designing a Safe Signature Migration Architecture
The most practical starting point is cryptographic agility: the ability to change authentication algorithms without redesigning an entire application or network.
1. Separate transaction authorization from signature verification
Applications should avoid embedding assumptions about one signature algorithm throughout their business logic. For example, a transaction authorization layer can define the intended operation, account, chain identifier, nonce, expiry, and execution parameters independently of the cryptographic verification mechanism.
A verifier then checks the signature against the account’s authorized authentication policy. The architecture can be represented as:
On smart-account systems, developers may implement multiple verification methods within the account’s authorization logic. On networks with fixed EOA verification rules, protocol-level changes or new account mechanisms may be necessary.
This separation reduces the number of components that must change during migration. However, it does not make a protocol quantum-resistant by itself: the underlying authorization mechanism must also reject vulnerable authentication paths when required.
2. Introduce versioned authentication policies
A wallet or smart account can use an explicit, versioned policy to identify its supported signature scheme. Such a policy might define:
The permitted algorithm and parameter set.
The public-key format and signature encoding.
The message serialization rules.
The conditions under which a signature is accepted.
The migration or recovery mechanism.
The signed message should bind authorization to the intended chain, account, operation, and nonce. This helps prevent cross-chain replay and reuse of a signature for a different operation.
Algorithm identifiers alone are insufficient. The verifier must enforce valid parameters, canonical encoding, and unambiguous message serialization. Otherwise, inconsistent interpretation between implementations can create security vulnerabilities.
3. Evaluate hybrid signatures carefully
One possible transition strategy is hybrid authentication, in which an operation requires both a conventional signature and a post-quantum signature. For example, a smart account might require both signatures during a migration period before eventually switching to post-quantum-only verification.
This approach can provide defense in depth, but its security depends on the exact verification policy. If the account accepts either signature, an attacker who can break the legacy scheme may still have a path to authorization. If both are mandatory, the system must correctly verify both and handle the failure of either verification process.
Hybrid authentication also increases signature size, execution costs, implementation complexity, and wallet integration requirements. It should therefore be introduced through a clearly defined threat model and rigorous testing rather than treated as an automatic upgrade.
Compatibility Risks That Can Break a Migration
Replacing a signature scheme changes more than cryptography. It affects every component that creates, transports, verifies, or stores signatures.
Transaction formats and fee economics
If a transaction format assumes a fixed signature length or a specific elliptic-curve encoding, larger post-quantum signatures may require new transaction types or protocol rules.
Developers should benchmark transaction serialization, signature verification, block propagation, and worst-case execution costs. They should also test denial-of-service scenarios in which malformed transactions attempt to trigger disproportionately expensive verification.
On public blockchains, increased signature size can also raise transaction fees or put pressure on block limits. These costs must be measured under realistic network conditions, not estimated from cryptographic benchmarks alone.
Legacy contracts and external integrations
Smart contracts may contain ECDSA-specific verification logic. Bridges, exchanges, relayers, custodians, and institutional wallets may independently assume a particular signature format. Upgrading a wallet therefore does not automatically make every connected application quantum-resistant.
Engineering teams should inventory these dependencies and determine whether each requires a contract upgrade, a new verification path, or a protocol-level change. They should also verify that external systems agree on the algorithm, signature encoding, and message format.
Dormant accounts and recovery failures
Migration requires control of the account or an explicitly authorized recovery mechanism. Lost keys, abandoned wallets, inaccessible hardware devices, and outdated multisignature policies can leave assets difficult or impossible to migrate.
Protocols must decide how to handle accounts that never migrate. Freezing legacy accounts, forcing transfers, or introducing recovery mechanisms creates security, governance, and ownership implications.
There is no universal solution for dormant accounts. Migration plans must account for users who cannot upgrade immediately without introducing arbitrary asset seizure or weakening account authorization.
A Practical Migration Roadmap for Blockchain Teams
Founders and engineering leads should treat post-quantum readiness as a phased engineering program.
1. Inventory cryptographic dependencies. Identify ECDSA, EdDSA, BLS signatures, elliptic-curve commitments, signature-verification contracts, wallet libraries, bridges, and custody systems. Not every cryptographic primitive has the same quantum risk, so classify each dependency individually.
2. Prioritize high-risk components. Focus on high-value keys, long-lived assets, critical infrastructure, and systems that cannot be upgraded easily. Document the assumptions each component makes about keys and signatures.
3. Build a replaceable authentication layer. Separate business authorization from algorithm-specific verification wherever the protocol permits. Define versioned formats and strict verification rules.
4. Prototype standardized algorithms. Evaluate ML-DSA and SLH-DSA using vetted implementations. Measure signature size, verification latency, memory consumption, throughput, and interoperability across supported platforms.
5. Test migration and recovery. Simulate legacy transactions, mixed-version clients, interrupted upgrades, failed key rotation, and account-recovery scenarios. Include malformed signatures, replay attempts, and resource-exhaustion tests.
6. Deploy through controlled stages. Use test networks, security reviews, and formal verification where appropriate. Establish explicit activation criteria, monitoring, emergency procedures, and a documented migration path before production rollout.
For Ethereum-based projects, monitor the Ethereum Foundation’s post-quantum research and the Ethereum quantum-resistance roadmap. These resources describe ongoing research and evolving plans, not guarantees that every proposed feature will be available by a particular date.
Conclusion: Prepare for Change Without Introducing New Risks
Post-quantum blockchain security is not achieved simply by selecting a quantum-resistant signature algorithm. It requires compatibility across wallets, contracts, validators, transaction formats, custody systems, and recovery processes.
The strongest preparation starts with cryptographic agility, dependency mapping, measurable performance testing, and a migration strategy that protects users who cannot upgrade immediately.
Quantum-resistant cryptography is becoming an important engineering consideration, but rushed implementations can introduce vulnerabilities of their own. Blockchain teams should begin by understanding their cryptographic dependencies, testing standardized alternatives, and designing migration mechanisms that preserve authorization and asset access.
For B2B founders, the strategic question is not only whether a protocol can adopt new signatures. It is whether the entire ecosystem can adopt them without compromising asset ownership, network performance, or trust.
Core DAO’s early contributors Rich Rines and Brendon Sedo have stepped down from their roles in the DAO as the Bitcoin-focused blockchain transfers more responsibilities to independent validators and community members. In an October 27 announcement on X, Core DAO…
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