Automatically score how consistent your AI agent's answers are

Compares your AI agent's answers to known correct answers and scores how closely they match, so you can catch drift.

How the work actually flows

A straight line. Runs once per each test question.

Pattern: Sequence (1) ยท Multiple Instances with a priori Design-Time Knowledge (13)

flowchart TD trig(("run test question set")):::human s0[["compare to expected answer"]]:::mi s1["produce similarity score"]:::task trig --> s0 s0 --> s1 out[/"similarity score per question"/]:::out pay{{"catch ai answer drift early"}}:::pay s1 --> 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 stepRuns once per itemA personResultPayoff
Build size
Advanced

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

Business functions
AI Agents & Autonomous SystemsAI Chatbots & AssistantsKnowledge Base & RAGReporting & Analytics
Connects
OpenAI

The problem it solves

You've built an AI assistant or chatbot for your business, but you have no easy way to know if it's still giving accurate, consistent answers as you make changes. A subtle model update or prompt tweak can quietly make your AI worse without anyone noticing until a customer complains.

Who it fits

Teams running an AI chatbot or assistant who want an ongoing check on answer quality and consistency.

How it works

  1. Runs a set of test questions with known correct answers through your AI agent
  2. Generates the AI's response for each question
  3. Compares the AI's answer to the expected answer using similarity scoring
  4. Produces a score showing how closely the AI matched the correct answer
What you get

Answer drift you catch before customers notice

You get an ongoing score showing how closely your AI agent's answers match the correct ones, so drift gets caught early.

What you get

A similarity score for each test question, flagging where the AI's answers are drifting from the expected results.

What you need

An OpenAI API key and whatever platform hosts your AI agent.

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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