About Credible

The company behind the AI context engine

Modern data systems are powerful but fragmented. Meaning — definitions, metrics, institutional knowledge — is scattered across dashboards, SQL, and people's heads. Credible was founded to change that.

Our mission

To make data matter

Data only matters when the people and AI using it understand what it means. Credible is an AI context engine that captures what your data means — definitions, metrics, and institutional knowledge — and delivers your data and its meaning as context, to your AI agents, your dashboards, and your product.

Built on the open-source modeling language Malloy, Credible combines an open standard with the workflows and governance needed to make data models practical at enterprise scale — we make them fast, secure, and efficient.

Our story

Thirty years in the making

Credible was founded by Kyle Nesbit, who spent seventeen years at Google building the foundation of Google Cloud's data analytics stack — from BigQuery's backplane to AI and semantic modeling for business intelligence.

As the uber tech lead integrating Looker into Google Cloud, Kyle got to know Lloyd Tabb, Looker's founder and the creator of LookML. Lloyd was building Malloy, the open-source successor to LookML — thirty years of semantic data modeling experience distilled into one open language.

Kyle brought Malloy into BigQuery — and learned firsthand how hard it is for a large company to bet on technology that disrupts its own products. The classic innovator's dilemma: the idea was ready, but it would take a new company to see it through.

Across his time at Google, Kyle watched complexity pile up: sprawling pipelines, overlapping tools, semantics littered across systems that were never intended to convey data's meaning. When AI arrived as a consumer of data, that complexity became untenable: models can't reason over data they don't understand. Kyle knew there was a simpler, more elegant way to build a data stack for the AI era.

In 2025, Kyle left Google to build that simpler stack. He started with Malloy Publisher, the open-source server for Malloy semantic models, and created Credible around it: a context engine designed from the ground up for a world where AI is a first-class consumer of data.

Our team

Founder-led, built in the open

We're a small team of engineers based in Boulder, Colorado. We've spent our careers building data and AI infrastructure at scale, and we build Credible the same way: open standards first, engineering rigor throughout, and no gap between the people who design the product and the people who use it.

We work in the open. Credible is built on Malloy, we maintain Malloy Publisher as an open-source project, and we're active members of the Open Semantics Interchange working group — because meaning belongs to the organizations that create it, not to a vendor.

Join us on the journey

Ready to make your data matter?

Whether you're deploying AI agents, building data products, or just tired of dashboards that disagree — Credible delivers your data and its meaning wherever decisions get made.