Test how different AI models handle your legal documents

Run the same legal document questions through several AI models at once and compare their accuracy in a spreadsheet.

How the work actually flows

It branches. Every path runs; runs once per one per test document.

Pattern: Multiple Instances without Synchronization (12) ยท Parallel Split (2)

flowchart TD trig[\"test documents listed in sheet"\]:::trigdata s0[["pull document from drive"]]:::mi s1["convert document to text"]:::task s2["send question to ai models"]:::svc trig --> s0 s0 --> s1 s1 --> s2 gx{"+ which ai model to query"}:::gate s2 --> gx p00["get answer"]:::task gx -->|"model one"| p00 p01["log to sheet"]:::task p00 --> p01 p10["get answer"]:::task gx -->|"model two"| p10 p11["log to sheet"]:::task p10 --> p11 p01 --> out p11 --> out out[/"spreadsheet comparing model accuracy"/]:::out pay{{"confidence in which model to trust"}}:::pay 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 serviceRuns once per itemEvery pathResultPayoff
Build size
Advanced

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

Business functions
Document Processing & OCRSpreadsheet & Database OpsFile & Cloud Storage
Connects
Google SheetsGoogle DriveOpenRouter

The problem it solves

If you're relying on AI to read or extract information from legal documents, you need to know which model actually gets it right before trusting it with real work. Testing that by hand, one model and one document at a time, is slow and easy to lose track of.

Who it fits

Legal teams or operators evaluating which AI model to trust for document review and extraction tasks.

How it works

  1. You list your test documents and questions in a Google Sheet
  2. For each one, the system pulls the source file from Google Drive and converts it to text
  3. The text and question are sent to several AI models at once
  4. Each model's answer is logged back into the Google Sheet
What you get

Model answers compared side by side

See exactly how different AI models handle your legal documents, with every answer logged neatly in one spreadsheet for comparison.

What you get

A Google Sheet comparing how each AI model performed on the same set of legal documents.

What you need

A Google Sheets account, a Google Drive account, and an OpenRouter 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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