Avoid cloud embedding lock-in with a local, privacy-first embeddings runtime

Avoid cloud embedding lock-in with a local, privacy-first embeddings runtime targets a $6.0B = 2M businesses × $3K ACV for AI embeddings & RAG infrastructure per year total addressable market with medium saturation and a year-over-year growth rate of 40% YoY (source: aggregated estimates from Grand View Research and MarketsandMarkets on AI infrastructure and vector search growth).

Key trends driving demand: Open-source embedding and quantized model improvements — they make local and edge inference feasible and cost-effective for production use.; RAG adoption across support, docs, and analytics — teams increasingly need reliable, private embeddings tied to proprietary data.; Rising hosted API costs and unpredictable billing — cost control is motivating companies to evaluate self-hosting.; Privacy and compliance pressures — regulations and client requirements are forcing on-prem or private-cloud solutions for sensitive corpora..