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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.
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.
This article was written by the News Desk and edited by Samuel Rae.
Summary Bullets:
• As telemetry arrives, Observe adds structure that reflects each customer’s business, creating a context graph, which gives an AI agent a roadmap for querying data.
• Querying a structured database is quicker and burns far fewer tokens, which helps address the AI cost concerns that are top of mind among enterprises.
The need to manage costs and recognize a positive ROI are top concerns among organizations rolling out generative and agentic AI. Even the largest enterprises are taking a more careful look at token economics as they seek to scale the use of AI tools throughout their organizations. As employees, developers and agents all gain access to generative AI and use an ever-growing number of tokens, spending is skyrocketing. During the Snowflake World Tour 2026 in New York City in October, Jeremy Burton, former CEO of Observe and currently General Manager of Snowflake’s Observability business, notes that companies let chaos reign while they experimented with AI and now need to rein in token usage. One often-overlooked lever is context. The context graph helps agents investigate operational telemetry more efficiently, which can improve answers and reduce token usage in those workflows. For this reason, the impact of Snowflake’s acquisition of Observe, which helps organizations better structure and understand how data is being used, has the potential to manage overall enterprise AI spending as well.
Snowflake’s acquisition of Observe expands its observability portfolio. As telemetry arrives, Observe adds structure that reflects each customer’s business, creating a context graph that maps semantics and relationships across logs and metrics, which gives an AI agent a roadmap for querying data. An agent could dig through raw data, but querying a structured database is quicker and burns far fewer tokens. As Observe puts it, the company does not have better AI; it has better data. Observe ingests data based on OpenTelemetry open standards and can store it in Apache Iceberg formats, providing greater flexibility and control. It uses object storage, elastic compute, and interoperable standards to meet customers’ requests for flexibility and cost sensitive solutions.
Observe complements Snowflake Cortex AI Gateway, announced in July 2026. The gateway governs how Snowflake and third-party agents access tools, models and data. It routes requests to approved models based on cost, quality, and latency; allocates spend to teams and workloads; sets limits; and records agent actions. Observe Agent Observability goes deeper, tracking which tools agents access and correlating agent activity with backend telemetry. It adds more detail directly from the agents themselves, such as connections to underlying application and infrastructure behavior. Observe stores the telemetry in Snowflake on low-cost object storage. At the scale of telemetry data, scan-based queries using Observe’s architecture are cheaper and faster than using index-based tools. Together, Cortex AI Gateway and Observe provide an end-to-end picture of an agent, from chat client to gateway to back end. Plenty of tools observe the agent itself; Observe provides deeper insight into the surrounding telemetry.
Improved context sits at the center of several trends related to how data is accessed. Software is going headless, as users prefer prompts and APIs to complicated interfaces when interacting with information. Walled gardens are crumbling as APIs, CLIs, and MCP streamline access to information and enable AI agents to drive actions. Evaluations, which interrogate how an agent reached its answer in testing and production, depend on rich telemetry. The next opportunity lies in context graphs. Enterprises that structure their data first can make more efficient use of tokens. With AI bills climbing, vendors that offer solutions that reduce token usage offer a compelling value proposition.
The post Snowflake’s Observe Helps Businesses Rein in Token Usage by Improving Context appeared first on IT Connection.
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Windows 11 offers controls for diagnostic data, location access, clipboard syncing, and personalized recommendations. Here's how to review seven privacy settings and understand their trade-offs.
The post 7 Windows 11 Privacy Settings You Should Check in 2026 appeared first on TechRepublic.
Windows 11 offers controls for diagnostic data, location access, clipboard syncing, and personalized recommendations. Here's how to review seven privacy settings and understand their trade-offs.
The post 7 Windows 11 Privacy Settings You Should Check in 2026 appeared first on TechRepublic.
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USAFacts — the nonpartisan civic data initiative founded by former Microsoft CEO Steve Ballmer — is stepping out of its usual spreadsheet-and-report routine and onto the debate stage, launching its first-ever YouTube debate special titled “The American Dream at 250: Data doesn’t argue. They do.”
The 75-minute program pairs conservative commentator and Daily Wire founder Ben Shapiro with progressive author and NYU Stern professor Scott Galloway to hash out escalating cost-of-living pressures and the viability of homeownership — all while tethering their arguments to official government numbers. PBS NewsHour co-anchor Geoff Bennett moderated.
Ballmer steers the effort from the organization’s Fact Desk, leaning into USAFacts’ core mission of grounding national political flashpoints in verified government numbers rather than partisan rhetoric.
“Americans can disagree about the role of government in their lives, but productive debate begins with a shared understanding of the numbers,” USAFacts President Lauren Woodman said in a news release Wednesday, explaining that the project is designed to give the public a common factual baseline to evaluate competing policy choices.
The debate focused on three core economic questions, using federal data as a launching pad:
Capitalism vs. government intervention: The debaters tackled whether free markets or government programs are better equipped to preserve the American Dream and address mounting economic pressures.
The scale of government: They sparred over whether Washington is currently doing too much or too little to intervene in the everyday lives and finances of citizens.
The housing crisis and homeownership: The discussion zeroed in on whether homeownership remains a realistic milestone of the American Dream for younger generations, and whether the government should step in to make housing more attainable.
Founded by Ballmer in 2017 with $10 million of his own money, Bellevue, Wash.-based USAFacts operates like a reporting unit for the public sector, aggregating statistics from over 70 federal sources.
The organization is best known for publishing annual corporate-style “10-K” reports on government revenue and spending, as well as running a data-driven “State of the Union” companion timed to the president’s annual address to Congress.
Watch the full debate below:
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Summary Bullets:
• AI-driven conversational discovery experience boosts the relevancy of marketplaces among broader audiences.
• Network services evolve into consumable and programmable products via enterprise agents.
Agentic AI innovations have boosted hyperscaler marketplaces’ relevance, and global telecommunications giants are taking notice.
Struggling for years on trying to fit a square peg into a round hole, telcos are recognizing the online storefronts as a prime route to sales growth by leveraging agentic AI to streamline enterprise delivery of network services. Factors range from agentic AI-driven product procurement through conversational discovery of solutions, to improved productization of infrastructure services.
Advancements in open-source software (OSS) have resulted in a greater number of carrier solutions being listed on marketplaces, alongside standardized APIs (enabled through MCPs, GSMA Open Gateway, and CAMARA) for streamlined connectivity. Networks (e.g., networks-as-code) are evolving and becoming more consumable and programmable via enterprise agents, with no complex coding or integration required by enterprises. Ericsson-led network-API operator alliance, Aduna, is a good example of such activities. Nokia’s contribution of Network-as-Code APIs to Google Cloud Marketplace is another.
Telcos are filling key roles through marketplace channels, including fulfilling private wireless deals, reselling software and platform services, and offering enterprise customers valuable consulting and integration services.
This infra productization couples nicely with another trend in marketplaces: Agent mode UX innovations have appeared across marketplaces. They support conversational discovery experiences for software procurement and are significant for their role in broadening the audience of less technical buyers.
Within the last year, AWS released two AI-powered tools for its marketplace: agent mode, which is its version of a conversational discovery experience for software procurement; and enhanced search. Buyers describe to the agent a use case, including specific requirements, to gather product details and compare options. These conversational queries in marketplaces are significant to sellers for their role in expanding the audience to include less technical buyers looking to solve their companies’ digitization issues.
Google and Microsoft also released chat-style methods to discover appropriate solutions on marketplaces. Google’s AI-powered search experience moves beyond keyword searches to provide users with natural-language discovery across its services and AI agent catalog. Its approach is similar to AWS by allowing users to describe their goals or a technical problem in order to better identify appropriate products, including third-party offerings. Microsoft brands its conversational AI experience as ‘intelligent discovery’, with interactive chat-enabled evaluation and comparisons of products.
A lot is at stake in the battle of the hyperscaler marketplaces, reported to be worth tens of billions of dollars, including partner solutions. AWS now claims over 30,000 product listings, including an AI Agents and Tools category launched last July and later that year, and agent mode for AI-enhanced search for buyers. Microsoft rebuilt its marketplace last September after merging its Azure Marketplace and AppSource. The storefront now includes over 3,000 AI apps and agents. Adding AI Agent Marketplace last year, Google differentiates on a cost basis, cutting its fee from a flat 3% down to 1.5% for certain deals. The marketplace wars will heat up as the telcos increasingly play in this space.
The post Agentic AI Transforms the Marketplace UX as Infra Services Become Consumable Products appeared first on IT Connection.
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