Reduce data-team documentation toil with a self-documenting semantic layer

Reduce data-team documentation toil with a self-documenting semantic layer targets a $12.0B = 200,000 mid+enterprise companies x $60K ACV (organization-wide semantic & docs + governance add-ons) total addressable market with medium saturation and a year-over-year growth rate of 18% estimated growth for metadata/semantic tooling and governance market segments.

Key trends driving demand: Cloud-first analytics -- rapid adoption of Snowflake/BigQuery/Databricks increases centralized metadata availability for automated tooling.; Data mesh & metric standardization -- pressure to publish trusted metrics pushes teams to adopt a centralized semantic contract.; LLM maturity -- large language models can now convert SQL and lineage into natural-language documentation and intent maps reliably.; Shift from manual catalogs to active semantic layers -- users want not-only-catalogs but actionable, queryable semantic models integrated with BI..