TL;DR: Birdeye has launched Peak, a subscription terminal combining digital-asset market data, fundamentals and portfolio analytics. Its pitch centers on consistent data across venues, rather than another isolated trading dashboard.

Institutional crypto researchers have another terminal to evaluate. Birdeye launched Peak on Wednesday, bringing several of its data and analysis services into one professional workspace.

The company’s October 21 announcement describes coverage spanning centralized and decentralized venues, with ETF flows, filings and private-funding information alongside on-chain data. Access is sold by seat and organization.

The official product page lists token supply and unlock information, holder concentration, wallet-level portfolio analysis, protocol metrics and institutional indices. A command-based interface lets users move between different objects and views, while a research layer called Peak AI is intended to surface connections across datasets.

The Value Depends On Consistent Definitions

Putting several data feeds into one screen can save time. It does not automatically make the figures comparable.

For a researcher examining an asset, circulating supply, fully diluted valuation and an upcoming unlock each describe something different. A wallet transfer might be a sale, a custody move or an internal reorganization. A large volume figure can also look more useful than it is if the methodology does not distinguish between types of activity.

Those are the practical problems an institutional terminal must solve if it is to support decisions beyond simple price monitoring. Users need to trace a number to its source and understand the assumptions behind it.

Birdeye says owning its on-chain indexing infrastructure lets it reconcile records and apply consistent definitions. That is the company’s explanation of its approach, rather than an independent audit of every metric delivered by Peak.

The product has not been performance-tested for this article, and the launch release does not establish that an AI-generated connection between datasets is a verified investment conclusion.

For prospective users, the relevant test will be whether the terminal makes research reproducible: can a colleague reach the same result, identify the same inputs and explain why the number changed? Peak’s launch puts that question in front of institutional desks with a new product built around it.

Related Reading

• Solana’s Tokenized Asset Market Grows More Than Sixfold In A Year
• Tokenized Stocks Reach $262 Million In DeFi, But The Growth Is Not All On Base
• Stablecoin Payments Reach $482 Billion As Token Supply Barely Grows

This article was written by the News Desk and edited by Samuel Rae.

Summary Bullets:

• Meta will need to shed its consumer-centric image to gain traction in the business market, even if it only targets smaller organizations.

• Convincing organizations that they can trust Meta to secure personal information and corporate intellectual property will take time and effort.

On Monday September 28, 2026, Meta announced plans to enter what is already a crowded enterprise AI market. It will develop Meta Enterprise Platform, a collection of tools and services that will help business customers implement their own AI strategies. Few details were shared other than the platform will incorporate Muse agent, Meta Business Agent, Muse API, Muse Code, and other solutions.

In addition to plans for an enterprise AI platform, Meta revealed it has developed a version of its Muse personal assistant for enterprises. Muse for Small Business, announced one day after Meta Enterprise Platform, expands on the consumer version of the Muse AI agent announced earlier this month. It can access a variety of enterprise applications, including Asana, Box, Canva, Dropbox, Figma, Granola, HighLevel, Intuit QuickBooks, Klaviyo, Lovable, Notion, Shopify, Slack, Stripe, Zoom, and Facebook and Instagram business accounts. A limited amount of Muse usage is available for free; customers that want to consume it at higher volumes can purchase subscription plans based on token usage.

Meta will need to shed its consumer-centric image to gain traction in the business market, even if it only targets smaller organizations. Bringing onboard a strong enterprise focused leader, Chirantan Desai, as the ‘Chief Enterprise Platform Officer’ is a good first step. The industry veteran has extensive experience gained at MongoDB, Cloudflare, and ServiceNow, which are well respected enterprise-focused brands. However, he will be fighting an uphill battle as he seeks to position Meta as a leading provider of enterprise-grade solutions. The Meta (and Facebook) brands are strongly associated with consumer services and devices, further bolstered by the recent buzz around its AI glasses and Meta Quest googles, which though intriguing, have yet to see serious application by the business community.

Furthermore, privacy concerns abound regarding Meta/Facebook. The company built a business model based upon the sharing of information, which is the antithesis of a corporate approach to data management. Convincing organizations of all sizes that Meta has the pedigree and experience to offer secure solutions to which they can entrust the personal information of customers and employees, as well as corporate intellectual property, will take time and effort.

Additionally, Meta is seeking to enter a very crowded market. All major software vendors, such as Oracle, ServiceNow, Microsoft, and Salesforce offer platforms on which their customers can create AI agents. And most claim to integrate with outside data sources. The large hyperscale cloud providers are already major players in the enterprise AI platform space, with Google and AWS positioned as leaders in GlobalData’s latest Cloud-based Enterprise AI Platform Competitive Landscape Assessment report.

Out-of-the-box solutions that can be customized are only a fraction of what is required for a successful enterprise AI strategy. Leaders in the market for enterprise AI platforms need to demonstrate they have the tools to implement responsible AI, including guardrails and harnesses for agentic AI. They will also need to offer observability and orchestration across agents and language models, as well as integration with predictive AI. And as implementations become more complex, the ability to offer professional services, whether in-house or in partnership with consultants and systems integrators, will be critical to helping customers deploy a strategy that focuses on value and business outcomes.

The post Meta Will Need to Shed its Consumer-centric Image to Gain Ground in Enterprise AI appeared first on IT Connection.

Discover how Cisco Secure Firewall 200 Series modernizes branch security with AI-powered threat detection, encrypted visibility, SD-WAN, and simpler management.

TL;DR

• Bybit has launched Bybit Odds, a product for tracking prediction-market probabilities and sentiment.
• The launch campaign includes a 17,000 USDT reward pool.
• Bybit Odds is an analytics product integrated into the exchange, not a standalone decentralized prediction-market protocol.

Bybit is moving into prediction markets without launching a new betting chain or standalone venue.

The exchange has introduced Bybit Odds, an analytics product designed to surface probability and sentiment data from prediction markets inside its own trading ecosystem.

Prediction Data Becomes Another Trading Signal

Bybit says the product aggregates real-time odds and presents them through probability visualizations and sentiment tools.

That positions prediction-market data as another input for traders alongside price charts, funding rates and order-book signals.

The launch also includes a 17,000 USDT promotional reward pool for early users.

The interesting part is not the campaign itself.

It is the way prediction markets are increasingly being treated as a data source rather than a separate category of product.

Bybit Odds Is Not A New Decentralized Market

Users should keep the product’s role straight.

Bybit Odds does not create a new blockchain-based prediction market where users mint positions or settle events through a decentralized protocol.

It is an analytics layer integrated into Bybit.

That makes it closer to a market-intelligence feature than a standalone prediction exchange.

Still, the launch says something about where trading platforms think demand is going.

Probability markets are becoming mainstream enough that a major crypto exchange now considers their data worth packaging directly for active traders.

This article was written by the News Desk and edited by Samuel Rae.

Replacing CISO Burnout with Data-Driven Certainty The Ultimate Decision Maker CISOs and security decision-makers are being crushed under an untenable expectation: achieve near-perfection in an era where cyber risks increase...

The post Innovator Spotlight: Level 6 Cyber appeared first on Cyber Defense Magazine.