Turn your documents into a chatbot that answers from them

Upload your own files and get a chatbot that answers questions using only what is in them.

How the work actually flows

A straight line. Runs once per each document chunk.

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

flowchart TD trig(("documents pointed to system")):::human s0[["chunk and embed documents"]]:::mi s1(("ask question in chat")):::human s2["retrieve relevant chunks"]:::svc s3["generate answer with ai"]:::task trig --> s0 s0 --> s1 s1 --> s2 s2 --> s3 out[/"chatbot answering from own documents"/]:::out pay{{"stop repeating the same answers"}}:::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 stepAn outside serviceRuns once per itemA personResultPayoff
Build size
Advanced

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

Business functions
AI Chatbots & AssistantsKnowledge Base & RAGFile & Cloud Storage
Connects
CohereGroq

The problem it solves

You have manuals, policies, or notes scattered across files, and finding the right answer means searching through documents by hand every time. New hires and customers end up asking you the same things because the information is buried.

Who it fits

Any small team that wants a searchable assistant built from their own documents instead of a generic chatbot.

How it works

  1. You point the system at your source documents
  2. The documents are broken into chunks and turned into searchable AI embeddings
  3. Someone asks a question in the chat
  4. The system finds the most relevant chunks and uses an AI model to write an answer
  5. The answer appears in the chat, grounded in your own material
What you get

Answers pulled straight from your own files

You get a chatbot built from your own documents that answers questions using only your material.

What you get

A working chatbot that answers questions from your own document library.

What you need

Accounts for an AI embedding provider and an AI language model provider.

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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