Intelligence without context
is not intelligence at all
We are building the context layer that makes AI useful.
The dominant AI narrative has a blind spot.
It treats intelligence as a general-purpose capability: something you can measure on benchmarks and deploy universally. But we'd never accept that logic for a human.
Your best hire wasn't exceptional because of their test scores. They became exceptional by applying their intelligence in context. Learning the environment, absorbing what was unspoken, understanding what mattered to whom and why. We call this learning on the job and we've never given AI the same foundation.
So we get the numbers we deserve: MIT found only 5% of generative AI pilots achieve revenue acceleration. IDC reports 88% never reach production. The models are brilliant, but they struggle in enterprises. The fault is not in the models. The fault is in how we think about intelligence.
Intelligence is never general. It is always for something, in some situation, for some purpose.
What makes it useful is Contextual Intelligence: the quality of AI reasoning that emerges when a system operates with full knowledge of the environment it's in.
This is the next frontier. We are building the company brain that takes AI from smart to useful.
Our Story
2020
The Context Layer for Data
Before Atlan, we were a data team tackling ambitious data projects for the UN, the Gates Foundation, and the Government of India. But internally, every day felt like chaos. We realized that every time data moved across teams or tools, context was lost.
We launched Atlan publicly in 2020 as the context layer for data, with the belief that shared context would help the humans of data, do their life's best work.
2023
The First AI Agent for Context
Atlan AI was the first AI agent to create context, built in partnership with Microsoft Azure and Open AI. It generated descriptions and READMEs for data assets based on SQL logic. Our customers loved it, generating 290K descriptions in a year with a 90% acceptance rate.
"Atlan AI changed how we approach documentation — instead of a never-ending backlog, our analysts trust AI-generated descriptions enough to make decisions on them every day."
Oliver Gomes
VP, Analytics & Strategy, Fox
Atlan AI was built for human-assisted workflows, where humans could review every AI output. But to make enterprise AI useful, we needed more context than humans could manually write or even review with Atlan AI. And enabling this needed a new kind of underlying infrastructure that no existing catalog or graph could solve.
2024
Rebuilding Context Infrastructure for the AI Era
Until then, all context infrastructure — data catalogs, business glossaries, wikis — was designed for humans. AI had changed that equation. Agents were now producing and consuming context.
We rebuilt our infrastructure from the ground up and introduced the Context Lakehouse. The first context infrastructure architecture built for the AI era: Iceberg-native, open, and built for agent speed.
We raised $105 million led by GIC and Meritech Capital to build the context layer for AI, bringing total funding to over $200 million. Revenue grew 7x over two years. Enterprise sales grew 400% in Q1 2024. Competitive win rate: 75%.
2025
The Only Leader Across Every Context Category
Named a Leader in The Forrester Wave™ for Enterprise Data Catalogs and Data Governance Solutions.
Leader for six consecutive quarters, ranked #1 across five categories.
Named a Leader in the Magic Quadrant for Metadata Management Solutions and Data & Analytics Governance Platforms.
2025
The First Ever Conference on Context
Re:Govern, the world's first conference on context, brought together data and AI leaders from Mastercard, Workday, CME Group, General Motors, Virgin Media O2, Nasdaq, GitLab, Dropbox, Elastic, easyJet, and more.
2026
The Infrastructure for Contextual Intelligence
Atlan's context lakehouse has become the primary consumption interface for AI agents operating with context.
Context Agents hit a tipping point. In just two weeks across 50+ enterprises, they produced four times the volume of documentation those organizations had written by hand in an entire year.
1.03M
Descriptions Generated
87%
Human Parity Quality
110k+
Hours Saved
50+
Enterprises Active
AI teams at Workday and Fox achieved a 5x improvement in AI accuracy by engineering context the way AI actually needs it: versioned, tested, and deployable across every agent simultaneously.
Intelligence, without context, isn't intelligence at all.
