Test and score your AI workflows before you trust them

Runs test examples through your AI workflow and scores its accuracy and helpfulness so you know it's reliable.

How the work actually flows

A straight line. Runs once per one per test example.

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

flowchart TD trig(("user runs evaluation suite")):::human s0[["run test examples"]]:::mi s1["check answers against expected"]:::task s2["review tool use and helpfulness"]:::task s3[("track results over time")]:::store trig --> s0 s0 --> s1 s1 --> s2 s2 --> s3 out[/"running accuracy scorecard"/]:::out pay{{"confidence before AI faces customers"}}:::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 stepRuns once per itemA personA record or sheetResultPayoff
Build size
Advanced

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

Business functions
AI Agents & Autonomous SystemsEmail AutomationDocument Processing & OCRSpreadsheet & Database OpsEducation & Training
Connects
Google SheetsOpenAIAnthropic

The problem it solves

You've built AI into part of your business, but you have no systematic way to check whether it's actually giving accurate, on-topic, helpful answers before it starts talking to customers or making decisions for you.

Who it fits

A business running AI-powered workflows who needs confidence they're working correctly.

How it works

  1. A set of test examples is run against your AI workflow
  2. The AI's answers are checked against expected categories and correctness
  3. The system reviews whether the right tools were used and the response was helpful
  4. Results are tracked over time so you can see if changes help or hurt performance
What you get

Workflow answers you know are trustworthy

You get an automated check that scores how accurate and helpful your AI workflow's answers really are.

What you get

A running scorecard showing how accurate and reliable your AI workflow is over time.

What you need

An OpenAI or Anthropic API key and a spreadsheet or data table of test examples.

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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