Enabling AI features
AI features built into Validio call your LLM provider with a credential that you configure. To set one up:- Turn on Allow LLM Credentials under Workspace > Settings > AI features. This requires global
settings:WRITEpermission. See Managing Workspace Settings. - Add a credential for your LLM provider. See LLM Credentials.
AI features in Validio
AI Description Generation
Generate contextual descriptions for catalog assets, schema fields, glossary terms, domains, validators, and lineage edges using your LLM credentials.
Debug Query Suggestions
Ask an agent to write an investigation query for an incident, drawing on the incident’s details, catalog metadata, and your saved debug queries.
Generating SQL in Validators and Filters
Compose and correct the SQL queries in custom SQL validators and SQL filters with an LLM, from a description in plain language.
Glossary Term Suggestions
Use AI to automatically discover catalog assets and schema fields that match a glossary term, using text matching, lineage analysis, and LLM refinement.
Lineage Edge Suggestions
Automatically suggest field-level lineage connections between cross-system assets using heuristic and LLM-powered matching.
Validator Recommendations
Streamline validator setup by automatically analyzing your data source to suggest tailored validators, windows, filters, and segmentations—powered by LLMs or statistical ML.
Validio MCP Server
The Validio MCP Server lets an AI assistant of your choice, such as Claude Desktop or Cursor, work with Validio through the Model Context Protocol. Your assistant brings its own model, so the MCP Server needs no LLM credential. Instead, an administrator turns on Enable MCP Server under Workspace > Settings > AI features.MCP Server Setup
Connect MCP clients directly to your Validio platform to help you configure validators, analyze incidents, and manage data quality, all through natural language conversation.
For details on what data AI features send to a Large Language Model, and how the MCP Server’s trust model differs, see AI Data Transparency.