About Credible

We build the engine.

The modern data stack was never designed. It piled up, one workaround at a time — and what your data means got scattered across all of it: dashboards, SQL, docs, and the heads of a few experts. Credible was founded to take the layers out. One engine that turns raw data into answers you can trust, for every person, agent, and application that asks. You build what comes next.

Our mission

Make data Credible

An answer is only worth acting on when the people and AI behind it understand what the data means. Credible is the AI Analytics Engine: you model your data's meaning, and the engine generates the rest — dashboards, data apps, semantic layer, pipelines, storage — so every agent, application, and person gets the same answer, fast. You own the what. The engine generates the how.

Built on Malloy, the open language the engine speaks, Credible adds the runtime, the workflows, and the governance that make a data model practical at enterprise scale — fast, secure, and efficient, and never locked to one warehouse. For the full technical story, read Inside the AI Analytics Engine.

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 data modeling for business intelligence. Integrating Looker into Google Cloud, he got to know Lloyd Tabb, Looker's founder and the creator of LookML, who was building Malloy: thirty years of data modeling 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. All the while he watched the data stack pile up, each layer a rational answer to a constraint of its time, and each another place for the data's meaning to scatter. When AI arrived as a consumer of data, the pile became untenable: an analyst fills a schema's gaps with judgment, an agent fills them with confidence. Kyle knew there was a simpler, more elegant way to build an analytics engine for the AI era.

In 2025, he left Google to build it. He started with Malloy Publisher, the open-source server for Malloy models, and built Credible around it: the AI Analytics Engine — not another layer on the stack but the engine that replaces it, 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: we maintain Malloy Publisher as an open-source project, and we're active members of Apache Ossie, the standard for exchanging semantic metadata — because meaning belongs to the organizations that create it, not to a vendor.

The Credible team on Pearl Street in Boulder, Colorado, with the Flatirons in the background

The AI Analytics Engine

Make your data Credible

Model your data's meaning, and the AI Analytics Engine delivers answers you can trust to every agent, data app, and dashboard that asks.