Datapace

Datapace is a semantic context layer for your databases. It automatically maps and documents any database, legacy or modern, into a living map of your data: the entities and relationships it holds, what each field means, how everything connects, its lineage, and whether you can trust it, through strictly read-only discovery. The map is built from three pillars, reconciled together: structure (schemas, tables, inferred relationships), meaning (business entities, a semantic layer over your data, sensitive-data detection, each proposal carrying a confidence score validated by your people), and usage (freshness, distributions, real query patterns). Nothing is marked trustworthy until a human confirms it. For your teams (BI, data science, architecture, governance), that map is the documentation you never had time to write: a data dictionary, a data model (ERD), end-to-end lineage, and classification by freshness and relevance. It enables your legacy databases for what's next, scoping migrations, cloud-warehouse projects, and AI with predictable cost instead of guesswork. For your AI agents and text-to-SQL tools, the same map becomes governed, trustworthy context, served through a standard context interface (MCP), so AI is accurate on real production schemas instead of clean demos.