Search long policies fast - embeddable RAG chatbot via one script tag

Search long policies fast - embeddable RAG chatbot via one script tag targets a $8.0B = 20M websites x $400 ACV. Rationale: estimate 20M SMB and midmarket websites that would pay for improved on-site self-serve document search at roughly $400/year for a basic embeddable plan. total addressable market with medium saturation and a year-over-year growth rate of 30% estimated annual growth for AI-powered site help widgets and RAG adoption in customer support and docs workflows.

Key trends driving demand: Self-serve support expansion -- companies increasingly prefer to deflect tickets and reduce live support headcount by improving on-site answers.; Hosted vector infrastructure -- vector DBs and managed embeddings reduce engineering cost to run RAG at scale.; Developer-first embeds -- faster adoption when install friction is minimal, evidenced by analytics/script-tag distribution patterns.; Privacy and data locality demand -- regulated industries require per-tenant control of documents and vectors, creating demand for privacy-aware embeddings..