Check how accurately your AI reads handwritten or scanned text

Compares AI-extracted text against the correct answer character by character, so you can measure how accurate your OCR really is.

How the work actually flows

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

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

flowchart TD trig[\"test image batch exists"\]:::trigdata s0[["extract text with ai"]]:::mi s1["compare to correct answer"]:::task s2["generate accuracy report"]:::task trig --> s0 s0 --> s1 s1 --> s2 out[/"accuracy score per test image"/]:::out pay{{"know exactly how reliable ocr is"}}:::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 stepRuns once per itemResultPayoff
Build size
Advanced

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

Business functions
Reporting & AnalyticsAPI & Webhook Integration
Connects
OpenAI

The problem it solves

You're using AI to read handwritten codes or scanned documents, but you don't actually know how accurate it is until something goes wrong downstream. Bad extractions can quietly corrupt records or trigger the wrong action.

Who it fits

Businesses using AI to extract text from images, forms, or handwritten documents.

How it works

  1. A batch of test images with known correct text runs through the system
  2. The automation downloads each image and uses AI to extract the text
  3. The extracted text is compared character by character against the correct answer
  4. Each test gets a similarity score
  5. You get a report showing how close the AI's readings are to the truth
What you get

OCR accuracy scored automatically

You get a report scoring how closely your AI's text extraction matches the correct answer, so you know how much to trust it.

What you get

A character-accuracy score for each test image and an overall accuracy report.

What you need

An OpenAI API key and an account for the automation platform running the extraction.

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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