16 docs tagged with "ai"

Establish robust AI governance frameworks that maintain compliance, mitigate risks, and drive trust through visibility, lifecycle management, and policy enforcement

Complete configuration reference for AI policy properties and settings in personas.

Integrate, catalog, and govern Amazon SageMaker AI assets in Atlan.

Integrate and leverage Atlan AI capabilities for enhanced data documentation, and lineage analysis.

Security and compliance information for Atlan AI, including AI architecture, data handling, encryption, model management, and compliance frameworks.

Automate metadata enrichment at scale using AI-powered context agents that generate descriptions, READMEs, and SQL intelligence across your most important data assets.

Bootstrap, test, and ship the business context every AI agent needs to produce accurate, trustworthy answers.

Step-by-step guide to triggering AI-powered metadata enrichment using context agents in Context Agents Studio.

Answers to common questions about Context Agents Studio—covering enrichment behavior, collections, agent support, processing time, and AI credit usage.

Learn what the Atlan MCP server is, what it enables, and how to connect using Remote or Local setup.

Set up the atlan-lakehouse agent skill to query Lakehouse using natural language in AI agents like Claude Code.

Understand the collections available in Context Agents Studio—curated groups of data assets automatically surfaced from usage signals to help you prioritize metadata enrichment.

Learn about the AI-powered context agents available in Context Agents Studio—specialized agents that generate descriptions, READMEs, and SQL intelligence.

Some capabilities shown here may require additional enablement or licensing. Contact your Atlan representative for details.

Learn what AI assets and metadata Atlan crawls from Amazon SageMaker.

Understand what Context Engineering Studio is, how it works, and the key concepts behind building and deploying context repositories.