RustyRAG

RustyRAG delivers on its promise of speed. The entire stack in Rust, inference on Cerebras and Groq, and parallelized retrieval/reranking/citation produce per-query latency that undercuts every competitor we've benchmarked. For agent loops requiring dozens of sequential calls, the difference is stark: RustyRAG completes 10 loops while competitors are still finishing their first. The integration story is strong: TypeScript and Python SDKs are well-documented, and the native MCP server slots into any MCP-compatible agent host instantly. The ingestion pipeline handles messy real-world documents (PDFs, scans, tables, web pages) via Docling, with auto-refresh when source files change. Shared collections with role-based access and per-workspace observability round out the enterprise appeal. Where RustyRAG falls short is transparency. Pricing is entirely behind a demo call, with no published tiers or rate limits. For small teams or individual developers, this friction may be a dealbreaker. There is no free tier or trial. The platform is cloud-only—no on-premise option is mentioned, though enterprise customers may negotiate it. RustyRAG does not support bring-your-own-LLM or fine-tuning, so you are locked into their model hosts. For teams that need custom models or on-prem deployment, alternatives like Vectara or Pinecone with your own LLM may be a better fit. Overall, RustyRAG is a specialist tool: if sub-second latency is critical and you can afford a sales call to get pricing, it's a strong choice. For hobbyists or price-sensitive teams, the lack of self-serve pricing is a major barrier.