Replace heavyweight vector DBs with file‑first retrieval for agent context

Replace heavyweight vector DBs with file‑first retrieval for agent context targets a $3.6B = 1.2M software teams × $3K ACV (developer tooling + agent retrieval add‑ons) total addressable market with medium saturation and a year-over-year growth rate of ≈30% YoY — driven by growth in AI developer tooling and RAG adoption (industry reports and vendor growth announcements).

Key trends driving demand: Trend — teams are embedding AI into workflows quickly, creating demand for lightweight retrieval solutions that reduce cost and latency.; Trend — developers increasingly prefer local/offline capabilities and privacy-preserving architectures, creating room for file-first tools.; Trend — popular frameworks (LangChain, LlamaIndex) make retrieval modular, enabling alternatives to vector DBs to plug in easily.; Trend — rising cost scrutiny and predictable billing demand push teams to seek simpler, more auditable retrieval stacks..