Atlan is the context layer for enterprise AI. It sits between business systems and AI agents, connecting lineage from data pipelines, business definitions from BI tools, SQL logic, knowledge from SOPs, quality scores, and access policies into a unified context store. Every agent and analyst queries that context store directly, eliminating manual context-building per use case.
Key Features
- Context Engineering Studio: Design and manage context for AI agents.
- Context Lakehouse: Unified metadata lakehouse for portable context.
- Context Agents: Auto-generate descriptions, metrics, and ontology across the data graph.
- Data Governance: Enforce policies at the asset level.
- AI Governance: Ensure traceability and compliance for AI outputs.
- App Framework: Build custom context-driven applications.
- 80+ Native Connectors: Connect to Snowflake, Databricks, BigQuery, dbt, Airflow, Tableau, Looker, Power BI, Postgres, and more.
Who It’s For
Atlan is used by AI leaders, data engineers, governance teams, and AI platform teams at enterprises including General Motors, Workday, Nasdaq, Mastercard, and Virgin Media O2.
Analyst Recognition
Gartner named Atlan a Leader in the 2025 Metadata Management and 2026 Data and Analytics Governance Magic Quadrants. Forrester did the same in its 2024 Enterprise Data Catalogs and 2025 Data Governance Solutions Waves.
Key Benefits
- Connects to 80+ enterprise systems including Snowflake, Databricks, BigQuery
- Recognized as a Leader by Gartner and Forrester in metadata management and data governance
- Context Agents auto-generate descriptions and metrics across the data graph
- Open and portable context layer prevents vendor lock-in