A London startup has secured €4.48 million ($5 million) to solve a growing headache for businesses: AI tools that spit out conflicting numbers. Querio launched today with a platform designed to keep every AI assistant in a company singing from the same data sheet.
The seed round was led by BMW i Ventures, with participation from Jason Calacanis’s LAUNCH fund, Haatch Ventures, Araya, Forum Ventures, and Secways. Founded in 2024 by CEO Rami Abi Habib and CTO Javier Bonilla, Querio targets a problem that has emerged as employees increasingly turn to Claude, ChatGPT, and Slack for business answers.
Those tools often pull from different sources. As a result, a revenue question might yield three different figures depending on where it gets asked. Data teams then burn hours reconciling discrepancies instead of building new work.
Querio positions itself as the single source of truth for company metrics. The platform stores reports, definitions, and analysis in the data team’s own GitHub repository, rather than locking that logic inside a vendor’s product. Business users can ask questions in Claude, ChatGPT, or Slack and receive identical answers, the company says.
“For thirty years, analytics tools have kept a company’s logic inside the vendor’s product, where it’s hard to move and hard for AI to work with,” Abi Habib said. “Now everyone is asking data questions in Claude, Slack and wherever else they work, and they get three different revenue numbers.”
The platform also handles change management. When a field gets renamed in a CRM, for instance, Querio’s AI agent detects the change, updates all dependent reports and definitions, and sends the data team a single approval request. After sign-off, every connected tool reflects the same information.
Querio holds SOC 2 Type II certification and complies with HIPAA and GDPR. The company says it does not train on customer data and maintains no-training and no-storage agreements with its AI model providers. Current customers include OpenVPN and agree.com.
As enterprises multiply their AI tooling, the need for consistency across those systems will only intensify. Querio’s bet: centralizing data logic in GitHub gives data teams control while letting AI agents do the heavy lifting.
