Developer Kit

RAG Pipeline Builder

Generates a complete RAG pipeline with chunking strategy, embedding model selection, vector store setup, hybrid retrieval, and a quality evaluation harness. Useful for standing up production RAG without expert-level tuning. Engineers shipping LLM-backed document QA, search, or summarization features; AI engineers replacing naive semantic search with production RAG; founders building knowledge-base chatbots on proprietary content. most importantly — how to measure retrieval quality. Naive RAG implementations hallucinate confidently, retrieve irrelevant passages, or miss the right document entirely. A structured builder produces a pipeline with sensible defaults for the corpus plus an evaluation harness so regressions are visible.