Atlan

Atlan positions itself as the context layer for enterprise AI, sitting between business systems and AI agents to provide the business definitions, data lineage, and access policies that agents need to reason accurately. The platform connects to 80+ enterprise data systems and uses a combination of AI-generated context and human certification to build a shared understanding of an organization's data. Atlan reports being named a Leader in the 2025 Gartner Magic Quadrant for Metadata Management Solutions, the 2026 Gartner Magic Quadrant for Data & Analytics Governance, the 2024 Forrester Wave for Enterprise Data Catalogs, and the 2025 Forrester Wave for Data Governance Solutions.

What It Is

Atlan is an enterprise data catalog and context engineering platform that unifies metadata from across an organization's data stack — warehouses, BI tools, pipeline orchestrators, and business applications — into a living knowledge graph. That graph serves as the foundation for AI agents, enabling them to understand what data means, how it flows, and who can access it. The platform spans four core stages: unify (connecting systems via native connectors), bootstrap (AI agents auto-generate descriptions, metrics, and ontology), collaborate (human experts certify context), and activate (certified context flows to agents via MCP server, SQL, and open APIs).

The Context Pipeline Architecture

Atlan's architecture centers on what it calls the Enterprise Data Graph and Context Lakehouse — described on the site as the first context store engineered natively for AI, built on Iceberg-native, open formats with graph-plus-file architecture and vector-native AI search. The pipeline has four stages:

• Unify: 80+ native connectors pull lineage, query history, BI semantics, tags, and quality signals from Snowflake, Databricks, BigQuery, dbt, Airflow, Tableau, Looker, Power BI, and more.
• Bootstrap: Context Agents auto-generate asset descriptions, link business terms, generate metrics, and build semantic views and ontology from SQL query history and BI semantics.
• Collaborate: Domain experts resolve conflicts, annotate edge cases, and certify context before it ships to production.
• Activate: Certified context serves downstream agents and tools via an MCP server, SQL interface, open APIs, and an SDK. Evals and traces feed back into the pipeline.

Context Agents and AI-Assisted Documentation

Atlan's Context Agents are AI teammates that read the Enterprise Data Graph and generate documentation at scale. According to the company's About page, in a two-week period across 50+ enterprise customers, Context Agents produced over 1.03 million descriptions, with 87% rated at human parity or better, saving an estimated 110,000+ hours. The company also reports that in April 2026, Context Agents generated 690K+ descriptions across 50+ enterprise customers with 87% rated on par or better than human writing. The Context Engineering Studio allows AI teams to bootstrap, test, and ship business context to multiple agents simultaneously — the site states that AI teams at Workday and Fox achieved a 5x improvement in AI accuracy using this approach.

Company History and Funding

Atlan was founded by a team that previously ran data projects for the UN, the Gates Foundation, and the Government of India. The platform launched publicly in 2020 as a data catalog. In 2023, Atlan AI became what the company describes as the first AI agent to create context, built in partnership with Microsoft Azure and OpenAI, generating 290K descriptions in its first year with a 90% acceptance rate. In 2024, Atlan rebuilt its underlying infrastructure to introduce the Context Lakehouse and raised a $105 million Series C led by GIC and Meritech Capital, bringing total funding to over $200 million. The company reports revenue grew 7x over two years and enterprise sales grew 400% in Q1 2024.

Who Uses It and How It Deploys

Atlan is a cloud-delivered SaaS platform accessed via web and API. It is designed for enterprise data teams, AI platform teams, governance teams, and data engineers. The platform layers on top of existing catalogs such as Microsoft Purview, Snowflake Horizon, and Databricks Unity Catalog, pulling their metadata into a unified context layer rather than replacing them. Context stored in Atlan is portable across AI frameworks and vendors through open APIs and Iceberg-native formats. The site lists customer logos including Mastercard, Workday, Nasdaq, General Motors, Virgin Media O2, Dropbox, Autodesk, HubSpot, Fox, NHS, Medtronic, and others, with published case studies for several of these organizations.