Build a searchable AI knowledge base from your documents

Feeds your PDFs, web pages, and video transcripts into a private database so an AI can search and answer questions on them.

How the work actually flows

A straight line.

Pattern: Sequence (1)

flowchart TD trig(("user submits a document")):::human s0["extract content from source"]:::task s1["break content into chunks"]:::task s2["convert chunks to embeddings"]:::task s3[("store in searchable database")]:::store trig --> s0 s0 --> s1 s1 --> s2 s2 --> s3 out[/"searchable knowledge base built"/]:::out pay{{"instant answers from your own content"}}:::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 stepA personA record or sheetResultPayoff
Build size
Standard

A mid-size build with several tools working together.

Business functions
Knowledge Base & RAGCRM & Sales PipelineDocument Processing & OCRSpreadsheet & Database OpsAPI & Webhook IntegrationEducation & Training
Connects
Postgres

The problem it solves

Your best knowledge is scattered across PDFs, web pages, and video transcripts, and nobody can search across all of it at once. When someone asks a question, you either dig through files yourself or answer from memory, and new team members have no easy way to get up to speed.

Who it fits

Businesses or consultants who want to turn their own documents and content into a searchable knowledge base for an AI assistant.

How it works

  1. You submit a PDF, a web link, or a YouTube video
  2. The content is extracted and broken into structured chunks
  3. Each chunk is converted into a searchable format and stored in a private database
  4. The stored knowledge becomes available for an AI to search and answer questions from
What you get

Documents your AI assistant can search

You get your PDFs, web pages, and videos turned into a private, searchable base your AI assistant can pull answers from.

What you get

A private, searchable knowledge base built from your own documents and content.

What you need

A Postgres database with vector search enabled.

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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