Your Own Documents
Stop pasting the right page into the chat by hand. Search your SOP binder in your own words, get answers that point to the page they came from, and see what it takes to build one.Search by meaning over your own documents, retrieval-augmented generation (RAG) that answers from them with citations, and a small working build you can adapt.Embedding indexes and semantic search, the RAG pipeline (chunk, embed, retrieve, generate with citations), its failure modes and evaluation, and a stdlib reference implementation.
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- 017 min
Search Your SOP Binder in Your Own WordsSearch your SOP binder by meaning (semantic search)Semantic search over your documents: indexing, retrieval, hybrid rankingDoneDonedone
A new hire types "an inspector just walked in" and the binder's search finds nothing, because the SOP says "inspectors". Search by meaning fixes that. You will search a real demo binder both ways and watch where plain search fails.Keyword search only finds the exact words; search by meaning (semantic search) finds passages that mean what you asked. You will run both, live, over a demo SOP binder, see how it works in four steps, and learn when plain search is still the better tool.Lexical versus semantic retrieval run side by side on a demo corpus, the indexing pipeline (passage splitting, contextual embedding, vector index), pgvector as the default store if you already run Postgres, and hybrid search for identifiers.
- 028 min
Answers From Your Own DocumentsAnswers from your own documents (RAG), with the page they came fromRetrieval-augmented generation: grounding, citations, abstention, and where it failsDoneDonedone
Search finds the right pages. Add one more step, an AI that reads only those pages and answers from them, and staff get the steps plus the SOP they came from. It should also say "the binder does not cover this" when that is true. Here is how it works, what it got right on our demo binder, and where it goes wrong.Retrieval-augmented generation (RAG): search your documents for the passages that match a question, hand only those to an LLM, and have it answer from them with citations, or say they do not cover it. Real results from our demo binder, the failure modes, and when pasting the whole document is simpler.The RAG pipeline end to end, grounding and citation instructions, abstention when retrieval misses, measured results on a demo corpus, failure modes (retrieval recall, staleness, permissions, injection via documents), evaluation, and when long context beats retrieval.
- 038 min
Build a Small One for Your BinderBuild a small SOP answer tool: what it takes, and a working starting pointA reference RAG build: index, retrieve, answer, evaluate, in 160 linesDoneDonedone
What it really takes to have your own SOP answer tool: a folder of SOPs, one key, an afternoon of your tech person's time, and pennies. You get the decisions to make before anyone builds, and a small working program to start from.The decisions an operator makes before building (which documents, who can ask, who keeps them current), and a small, readable program your tech person can run on a sample binder in ten minutes, then point at your own and measure.A standard-library reference implementation over OpenRouter: paragraph chunking with titles, embedding index, top-k retrieval, a grounded and citing prompt with abstention, --dry-run, and a recall@k eval over labelled questions. What to change for production.