Turn a long document into a searchable AI knowledge base

Breaks a large document into sections, summarizes and indexes each one so an AI assistant can search it accurately.

How the work actually flows

A straight line. Runs once per each page in the document.

Pattern: Sequence (1) ยท Multiple Instances without Synchronization (12)

flowchart TD trig(("document imported for indexing")):::human s0["extract text from document"]:::task s1[["summarize each page in context"]]:::mi s2["convert summary to embedding"]:::task s3[("store embeddings in database")]:::store trig --> s0 s0 -->|"one per each page in the document"| s1 s1 --> s2 s2 --> s3 out[/"searchable AI knowledge base"/]:::out pay{{"accurate AI answers from document"}}:::pay s3 --> out out --> pay classDef task fill:#e7f6fe,stroke:#34b8f0,color:#2c2a29 classDef svc fill:#f6f8fa,stroke:#7c8795,color:#2c2a29 classDef mi fill:#e7f6fe,stroke:#0079a8,color:#2c2a29,stroke-width:2px classDef human fill:#fff,stroke:#0079a8,color:#0079a8 classDef store fill:#f6f8fa,stroke:#0079a8,color:#2c2a29 classDef trig fill:#00a4eb,stroke:#0079a8,color:#fff,font-weight:bold classDef trigtime fill:#00a4eb,stroke:#0079a8,color:#fff,font-weight:bold classDef trigdata fill:#8ad4f5,stroke:#0079a8,color:#06314c,font-weight:bold classDef gate fill:#fff,stroke:#e8a23d,color:#6b4708,font-weight:bold classDef out fill:#1f9d6b,stroke:#167a53,color:#fff,font-weight:bold classDef pay fill:#06314c,stroke:#021f33,color:#fff
A stepRuns once per itemA personA record or sheetResultPayoff
Build size
Advanced

A larger build with multiple systems, AI reasoning, and custom rules.

Business functions
AI Agents & Autonomous SystemsAI Chatbots & AssistantsKnowledge Base & RAGDocument Processing & OCRImage & Media Processing
Connects
GeminiQdrantFeatherless

The problem it solves

You have a manual, policy document, or reference guide that's too long for anyone, including an AI assistant, to search through reliably. Employees or customers keep asking questions whose answers are buried on some page nobody wants to dig through.

Who it fits

Businesses that want an AI assistant to answer questions accurately from a large internal document, like a policy manual or handbook.

How it works

  1. A large document is imported and its text extracted
  2. Each page is summarized in context with the pages around it
  3. The summary is converted into a searchable AI embedding
  4. The embeddings are stored in a searchable database
  5. An AI assistant can then pull accurate answers from the document on demand
What you get

A document your AI assistant can actually search

You get a large document broken down and indexed so your AI assistant can pull accurate answers from it on demand.

What you get

A searchable knowledge base that an AI assistant can query to answer questions accurately from your document.

What you need

A Featherless.ai account for AI processing, a Google account for Gemini embeddings, and a Qdrant vector database.

We can build this. But should you?

The hard question is not how to build it. It is whether this is the right thing to build first.

That is what a Fractional Chief AI Officer figures out with you, before anyone writes a line of code.

Let's Talk Strategy

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