Querio, a London-based analytics platform for data teams and their AI agents, launched on Tuesday, October 27, 2026, with $5 million in total funding from investors including BMW i Ventures, LAUNCH, Haatch Ventures, Araya, Forum Ventures and Secways. The company tackles a problem that has grown sharper as employees turn to AI assistants for business questions: when every tool works from a different version of a company’s numbers, people get conflicting answers, and data teams spend their time reconciling them instead of doing new work. Querio gives data teams one place to define what the company’s numbers mean, and keeps that work in the team’s own GitHub rather than locked inside a vendor’s product.
One Answer In Every Tool
The pitch is simple to describe and hard to deliver. Business users can ask questions in Claude, ChatGPT or Slack and get the same answer each time, because every tool draws on the same definitions that the data team owns. When the business changes, Querio’s AI agent updates the affected reports and definitions, and the data team approves each change before anyone sees it.
Rami Abi Habib, Querio’s co-founder and chief executive, illustrated the problem with a renamed field. Say sales renames a field in the customer relationship system. The revenue dashboard breaks, the Slack bot says no deals closed last week, and Claude gives a third number. With Querio, the agent spots the change, fixes everything that depends on it, and sends the data team one update to approve. After that, every tool gives the same answer.
That approval step is the product’s central design choice. Querio lets data teams hand more of the work to AI agents while a person stays in charge of every change that reaches the business, according to co-founder and chief technology officer Javier Bonilla. The company argues that businesses want to use AI with their data but need to trust the answer, and trust here means a human sign-off, not just a confident-sounding reply.
Why The Old Analytics Model Breaks
For thirty years, Abi Habib said, analytics tools have kept a company’s logic inside the vendor’s product, where it is hard to move and hard for AI to work with. That was tolerable when one dashboard was the single source of truth. It breaks when employees ask questions in half a dozen places, each with its own copy of the logic, and each capable of producing a plausible but different number.
Querio’s answer is to move the logic somewhere the data team already controls: their own GitHub repository. Reports, definitions and analysis live there, and the platform works with existing data warehouses rather than asking companies to migrate. The company says it is SOC 2 Type II certified, and that it works with companies including OpenVPN and agree.com, though it has not disclosed customer counts, pricing or revenue.
A Crowded Field With A Narrow Wedge
Querio is entering a crowded market. Every major AI assistant now wants to answer business questions, and every business intelligence vendor is adding AI features of its own. Querio’s wedge is deliberately narrow: it does not try to be the assistant or the dashboard, but the layer that keeps their answers consistent, owned by the data team rather than by any single AI provider.
That positioning also explains the investor list. BMW i Ventures brings industrial and automotive connections, LAUNCH brings Jason Calacanis’s early-stage network, and the rest of the syndicate spans European and United States venture capital. Five million dollars is a modest sum by current AI standards, which means the company will need to prove its wedge quickly, but it also means the team is not under pressure to chase growth at any cost in its first year.
Why It Matters
This matters because the AI assistant era has quietly created a data governance crisis. When one person asks Claude for revenue and another asks ChatGPT, and the answers differ, the problem is not the models but the missing shared definitions underneath them. Companies that cannot answer the same question the same way twice will struggle to trust AI with decisions that matter, while enterprises are wiring agents directly into their workflows and AI assistants are moving deeper into business software. Querio’s bet is that data teams, not AI vendors, should own that layer, and the same trust question is now facing every agent platform that acts on a company’s behalf.
Background
Querio is based in London and describes itself as the analytics platform for data teams and their AI agents, keeping a company’s reports, definitions and analysis in the data team’s own GitHub and giving business users consistent answers in Claude, ChatGPT and Slack. Teams can learn more and book a demo through the company’s website.
Source: Querio launch announcement
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