Build a custom AI search tool for your product data

Lets an AI assistant search, filter, and recommend results from your own product or review data on demand.

How the work actually flows

It branches. Exactly one path is taken.

Pattern: Exclusive Choice (4) · Simple Merge (5)

flowchart TD trig>"a question is submitted"]:::trig s0["check product database"]:::svc s1["apply filtering or grouping"]:::task s2["generate tailored answer"]:::task trig --> s0 s1 --> s2 gx{"× what kind of query"}:::gate s0 --> gx p00["apply filters"]:::task gx -->|"filter query"| p00 p10["group results"]:::task gx -->|"group query"| p10 p20["generate recommendations"]:::task gx -->|"recommend query"| p20 jn{"○ answer generated"}:::gate p00 --> jn p10 --> jn p20 --> jn jn --> s1 out[/"tailored answer returned to user"/]:::out pay{{"answers complex data questions instantly"}}:::pay s2 --> 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 itA stepAn outside serviceOne path onlyPaths rejoinResultPayoff
Build size
Advanced

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

Business functions
AI Agents & Autonomous SystemsKnowledge Base & RAGAPI & Webhook Integration
Connects
QdrantOpenAI

The problem it solves

Your team has a lot of structured data, like product listings or customer reviews, but standard AI search tools can only answer simple questions about it. When you need grouped results or recommendations, someone has to dig through the data manually.

Who it fits

Businesses that want an AI assistant to search their own structured data.

How it works

  1. An AI assistant or chat client sends a question
  2. The assistant checks your product or review database
  3. Filters, grouping, or recommendation logic is applied as needed
  4. A tailored answer is generated and returned
What you get

Questions answered instantly from your own data

You get an assistant that can search, filter, and recommend from your own product and review data on demand.

What you get

An AI assistant that can search, filter, group, and recommend results from your own data.

What you need

An account with a vector database provider and an OpenAI API key.

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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