Give customers instant, tailored answers from your knowledge base

An AI agent classifies each question and pulls a tailored answer from your own documents automatically.

How the work actually flows

It branches. Exactly one path is taken.

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

flowchart TD trig>"customer submits a question"]:::trig s0["classify question type"]:::svc s1["search knowledge base"]:::svc s2["write tailored answer"]:::task s3["deliver answer to user"]:::task trig --> s0 s1 --> s2 s2 --> s3 gx{"× what type of question"}:::gate s0 --> gx p00["search for facts"]:::task gx -->|"factual question"| p00 p10["search for analysis"]:::task gx -->|"analytical question"| p10 p20["search for context"]:::task gx -->|"opinion or context question"| p20 jn{"○ combine findings"}:::gate p00 --> jn p10 --> jn p20 --> jn jn --> s1 out[/"accurate answer pulled from own documents"/]:::out pay{{"faster tailored support without staff time"}}:::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 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 SystemsAI Chatbots & AssistantsKnowledge Base & RAGAPI & Webhook Integration
Connects
Google GeminiQdrant

The problem it solves

Customers and staff ask the same kinds of questions over and over, but every question is different in tone: some want quick facts, others want context or opinion. A single canned chatbot response feels robotic and often misses what people actually need, sending them back to you for a real answer.

Who it fits

A support team or customer-facing business that fields a high volume of varied questions from customers or staff.

How it works

  1. A customer or team member submits a question through chat or an app.
  2. The AI reads the question and figures out whether it needs a fact, an analysis, an opinion, or context.
  3. It searches your knowledge base for the most relevant material using that strategy.
  4. The AI writes a tailored answer using what it found.
  5. The person receives a clear, relevant response right away.
What you get

Answers pulled straight from your own documents

Whoever asks a question gets a tailored answer pulled straight from your own documents, matched to the kind of question they asked.

What you get

A tailored, accurate chat response pulled directly from your own knowledge base.

What you need

A Google Gemini API key and a Qdrant vector database 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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