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What is Atlan?
Atlan is the context layer for enterprise AI, built to solve the problem of AI agents failing in production due to missing business context. It unifies metadata, business definitions, lineage, and institutional knowledge from across an organization into a single, living graph. The platform connects to over 80 data sources, including warehouses, BI tools, and business applications, to automatically extract and organize context. Atlan's AI agents then bootstrap this context by generating descriptions, linking terms, and surfacing business questions. Human domain experts can review, annotate, and certify the context before it is served to downstream AI tools via SQL, APIs, or the Atlan MCP server. The tool is designed for data teams, AI engineers, and business analysts who need to ensure their AI agents reason accurately about company-specific data and processes. Atlan is recognized as a leader by Gartner and Forrester in metadata management and data governance.
AI Tool Review Summary
4.7/5
High, consistent, and on-brand
Clean and minimal
LLMNLPKnowledge Graph
To provide a unified context layer that enables AI agents to understand and reason about enterprise data accurately.
Integrates with 80+ data sources including Snowflake, BigQuery, Looker, and Tableau; supports SQL, APIs, and MCP server for downstream AI tools.
Freemium with paid tiers
Features with the highest value for users are highlighted here.
Enterprise Data Graph unification
AI-powered context bootstrapping
Human-in-the-loop certification
MCP server for agent activation
80+ data source connectors
Lineage and glossary management
Conflict resolution and annotation
Traceable AI outputs
Data Engineers
AI/ML Engineers
Data Governance Teams
Business Analysts
Chief Data Officers
Compliance Officers
Product Managers
Data Scientists
IT Leaders
Enterprise Architects
Free
$0/free
Up to 5 users Basic metadata catalog Community support
Starter
$19/monthly
Up to 20 users Automated lineage Email support
Weekly intelligence on AI strategy, operations, and market shifts. No noise. No narrative. Direct to your inbox.
Pros & Cons
Provides a single source of truth for business context that AI agents can query directly. Combines AI automation with human expertise to ensure context is both scalable and trustworthy.
Requires significant initial setup to connect all data sources and define business terms. May be overkill for small teams or simple use cases without complex data environments.
FAQs
Just Launched
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