Builds / Knowledge & RAG Base
Knowledge & RAG Base
Give every agent the same long-term memory.
Advanced build · Automation & data · 5 parts · Running cost: Free tiers + model usage
A retrieval layer your whole agent fleet shares: documents in, grounded answers out, with model routing so each query runs on the cheapest brain that can handle it.
What drives the cost: Low to medium — mostly infrastructure
Recommended after Meeting Ops.
The parts
Orchestration
LangChain — Tool. The framework wiring retrieval, tools, and models together.
Alternatives: LlamaIndex
Indexing
LlamaIndex — Tool. Best-in-class document ingestion and query pipelines.
Alternatives: LangChain
Model routing
OpenRouter — Tool. One API over every frontier model — route by cost and capability.
Fast inference
DeepSeek-V4.1-Flash — Model. Cheap, fast model for the high-volume retrieval calls.
Alternatives: DeepSeek-V4 Flash, Gemini 3.5 Flash-Lite
Compute
Modal — Tool. Serverless GPU compute for embedding and processing jobs.
Alternatives: Replicate, Together AI
Run this build
Start the build and it becomes a checklist: for each part, mark the one you already have, pick an alternative of the same kind, or compare the options side by side. Every part you confirm goes onto your stack, and the build is complete when every required part is filled.
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Not sure this is the right one? Run Smart Match or browse all builds.