Atlan4

Overview

Atlan is a unified metadata control plane designed to create an enterprise context layer for AI and data systems. It functions as a "context operating system" that connects business systems, pulls context across data estates into a living graph, and makes that context machine-readable for AI applications. The platform addresses the gap between scattered knowledge across enterprise tools and AI systems that need reliable, trustworthy context to operate effectively.

Key Features

Context Engineering Studio Bootstrap, test, and ship business understanding that AI needs. The studio reads existing data graphs to auto-generate semantic layers, allowing domain experts to refine definitions. It includes evaluation suites for testing context accuracy across different personas (data analysts, executives, engineers) and deployment capabilities that push context to multiple AI agents simultaneously.

Enterprise Data Graph Connects all business systems and consolidates context across the data estate into one living graph. Includes connectors to major platforms (Snowflake, BigQuery, Looker, dbt, Tableau, Confluence, Slack, Notion) and data lineage capabilities.

Context Agents AI teammates that document tacit knowledge and prepare data for AI readiness. Agents can read and write context across the stack, handling ontology, descriptions, metrics, quality, glossary, and README documentation.

Context Lakehouse Described as the world's first context store engineered natively for AI. Built on Iceberg-native architecture with open formats, graph+file architecture, and vector-native AI search capabilities.

Data Marketplace Provides humans with context they need to understand business data. Integrates with Slack, Teams, Claude, and ChatGPT to deliver context where teams already work.

Deployment Options Context can be deployed to multiple AI platforms including Cortex Analyst, Genie, Claude, ChatGPT, and Google Agentspace, ensuring consistent answers across different AI tools.

Use Cases

• AI Readiness: Preparing data and context for AI agents to produce accurate, trustworthy outcomes