Credible Data Raises $10 Million to Bring Trusted Business Context to Enterprise AI Data

Open-Source Malloy-Powered Platform Captures the Meaning of Enterprise Data, Delivers It As Context at Runtime to AI Agents, APIs, Analytics Tools and More

BOULDER, Colo., July 28, 2026 /PRNewswire/ -- Credible Data, the trusted business context engine for enterprise AI, today announced a significant acceleration in the scale-up of its platform following a $10 million seed round from Gradient, SignalFire and K5 Global, along with angel investors including G2 cofounder & CEO Godard Abel, pandas creator and Composed Ventures General Partner Wes McKinney, Snowplow Analytics CEO and co-founder Alex Dean, SV Angel and others. Built on Malloy, an open-source semantic modeling language, Credible's platform turns organization-specific governed metrics, definitions, entities, and relationships into executable business context that AI agents and applications can query, reuse and trust at scale.

Enterprises have made rapid progress giving AI agents access to unstructured and semi-structured data through documents and knowledge bases. Much of the data that actually runs the business, though, still lives in data warehouses such as Google BigQuery, Snowflake or Postgres. For AI to use this structured data reliably, it needs more than access to rows and columns; it needs the governed business meaning behind the data, including how metrics are defined, how entities relate, which rules apply, and who is allowed to see what. Without that business context, AI agents can produce inconsistent or incorrect answers from the same underlying data, undermining enterprise trust in AI.

Credible Data's context engine solves this problem by analyzing how an enterprise actually uses its data - informed by real queries and edge cases surfaced during use - to generate a universal, governable semantic model of organization-specific business context using Malloy. Credible Data's platform makes all of this context available to AI agents, analytics tools and other systems at runtime, enabling organizations to achieve trusted results from every element of their tech stacks while avoiding vendor lock-in and ensuring industry-leading flexibility and agility.

Credible Data CEO and founder Kyle Nesbit said, "Every organization attaches its own meaning to its data -- even a term as familiar as 'revenue' can mean completely different things from one company to the next. AI can't be trusted with enterprise data until it understands that meaning. The winners in enterprise AI will be the ones who deliver their data's meaning as context wherever decisions get made, without locking themselves into a single vendor's stack. That's what we've built at Credible Data."

Credible Data takes Malloy's semantic modeling foundation to enterprise scale, adding the security, role-based access controls, governance, reliability, auditability, and operational safeguards required for mission-critical analytics and high-volume agentic AI workloads.

Gradient General Partner Zach Bratun-Glennon said, "Existing data warehouse and pipeline solutions were never built for AI. As enterprises rush to deploy AI throughout their organizations, they are finding their ability to trust this new technology undermined by conflicting outputs stemming from a lack of consistent meaning applied to their data. Credible Data has built a platform that solves this challenge with unprecedented agility and flexibility, and which we believe will be fundamental in finally achieving trustworthy AI for enterprises."

Credible Data has assembled an exceptional team with deep industry expertise to pursue its mission. Nesbit previously led Business Intelligence and Data Analytics at Google Cloud and spearheaded Looker's integration into that platform; prior to that he led Forward Deployed Engineering at Gradient. Additionally, the company's Head of Product, James Swirhun, spent eight years at Google working on AI/ML products including Gemini; prior to that he was a consultant at Bain & Company.

Peter Nummerdor, SVP of Product for VideoAmp, a Credible Data customer, said, "Our planning and measurement drives decisions by some of the largest companies in the advertising industry, so every insight our AI gives has to be consistent, defensible and grounded in fact. Credible gives our AI systems the same governed understanding of our metrics that our best analysts carry in their heads. That's what moved us from experimenting with AI to putting it in front of customers with confidence."

About Credible Data
Credible Data is the engine for trusted business context on enterprise data. Built on Malloy, an open-source semantic modeling language, Credible turns governed metrics, definitions, entities, and relationships into executable context that AI agents and applications can query, reuse, and trust.

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SOURCE Credible Data