Load structured articles into an AI search database automatically

Pulls JSON articles from your FTP server, breaks them into chunks, and loads them into an AI-ready search database.

How the work actually flows

A straight line. Runs once per each downloaded article.

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

flowchart TD trig[\"new articles on ftp server"\]:::trigdata s0[("download json articles")]:::store s1[["split articles into chunks"]]:::mi s2["generate embeddings for chunks"]:::svc s3[("store chunks in vector database")]:::store trig --> s0 s0 -->|"one per each downloaded article"| s1 s1 --> s2 s2 --> s3 out[/"ai searchable article database"/]:::out pay{{"instant ai powered content search"}}:::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
Starts itAn outside serviceRuns once per itemA record or sheetResultPayoff
Build size
Advanced

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

Business functions
Knowledge Base & RAGCRM & Sales Pipeline
Connects
OpenAIQdrant

The problem it solves

Getting your content ready for AI-powered search or a chatbot means manually breaking articles into chunks, generating embeddings, and uploading them one at a time. Doing this by hand for a large library of articles simply doesn't scale. Any new content update means repeating the whole tedious process again.

Who it fits

Businesses building an AI-powered search tool or assistant on top of their own content library.

How it works

  1. The system connects to your FTP server and downloads new JSON articles
  2. Each article is split into smaller text chunks
  3. AI creates a searchable embedding for each chunk
  4. The chunks and embeddings are stored in your Qdrant vector database, ready for AI search
What you get

Content ready for AI search

Your articles get organized and loaded into a search-ready database automatically.

What you get

A fully indexed, AI-searchable database built from your article library.

What you need

An FTP server, an OpenAI API key, and a Qdrant account.

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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