Automatically infer table relationships and lineage to eliminate manual mapping

Automatically infer table relationships and lineage to eliminate manual mapping targets a $12.0B = 200K businesses × $60K ACV total addressable market with medium saturation and a year-over-year growth rate of 20% YoY (Gartner and industry reports identify metadata management and data cataloging growing ~20%+ as enterprises invest in governance and observability).

Key trends driving demand: Cloud data warehouse centralization — more organizations standardize on Snowflake/BigQuery/Redshift, creating a single place to extract metadata and add inference capabilities.; Analytics engineering adoption (dbt) — teams need faster feedback on model correctness and lineage, making automated mapping a natural complement.; Rising investment in data governance and observability — companies want trust and traceability in analytics, increasing demand for lineage and relationship mapping.; ML and LLM advances — new models can parse SQL and infer semantics from query history, enabling accurate relationship inference at scale..