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Analytics help you answer one practical question: can I trust this workflow’s results before I rely on them? Once you’ve verified some documents, the Analytics tab in each workflow shows you how well it’s performing — how reliable the results are, where errors tend to appear, and which fields need attention.
The short version: anyformat gives every value a confidence score so you know where to look — review the low-confidence ones first. Over time, your verifications produce an accuracy number that tells you how often the workflow is actually right. Aim for high accuracy with light review on the low-confidence cases — you don’t need to check everything.
The rest of this page explains both numbers in detail.

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Confidence

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What is confidence?

Confidence represents how certain anyformat is about an extracted value. It’s expressed as a percentage:
  • High confidence - the model is very sure
  • Low confidence - the value may be ambiguous or unclear
Confidence is calculated per:
  • Field
  • Document
  • Workflow (average)
Confidence score

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What confidence is (and isn’t)

Confidence IS

  • A signal, not a verdict
  • A way to prioritize human review
  • A guide for where to look first

Confidence is NOT

  • A guarantee of correctness
  • A replacement for verifying results yourself
  • A measure of business accuracy
A value can have:
  • High confidence and still be wrong
  • Low confidence and still be correct

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How to use confidence effectively

Use confidence to:
  • Focus review on low-confidence fields
  • Skip reviewing obviously reliable values
  • Reduce overall human effort
A good workflow doesn’t eliminate low confidence — it contains it.

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Accuracy explained

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What is accuracy?

Accuracy measures how often extracted values are actually correct, based on the documents you’ve verified.
Accuracy reflects confirmed correctness, not how sure the model felt.
Accuracy is calculated from:
  • Fields you verified as correct
  • Fields you corrected

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Accuracy vs confidence

ConfidenceAccuracy
How sure the model isHow often it’s confirmed right
Available immediately, before you check anythingBuilds up as you verify documents
A guess about each value, up frontA track record, after the fact
Helps you prioritize what to reviewMeasures real performance
You need both:
  • Confidence to guide review
  • Accuracy to judge quality

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What accuracy tells you

Accuracy helps you answer:
  • Can I trust this workflow?
  • Is it ready to scale?
  • Which fields are fragile?
Low accuracy usually points to:
  • Ambiguous instructions
  • Poor field definitions
  • Edge cases in documents

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Viewing analytics

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Workflow-level analytics

In the Analytics tab of a workflow, you can see:
  • Average confidence
  • Average accuracy
  • Trends over time (if available)
This gives you a high-level sense of workflow health. Analytics monitoring

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Field-level analytics

You can also analyze metrics per field:
  • Average confidence by field
  • Accuracy by field
  • Sort fields by performance
This is often the most useful view. It helps you quickly spot:
  • Fields that consistently fail
  • Fields that don’t need review anymore
  • Outliers dragging accuracy down

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Improving results

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How to improve confidence

To improve confidence:
  • Make instructions more explicit
  • Clarify where information appears
  • Reduce ambiguity in field definitions
  • Split complex fields into simpler ones
Confidence improves when field definitions become clearer.

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How to improve accuracy

To improve accuracy:
  • Correct wrong values while verifying
  • Review low-confidence fields carefully
  • Refine the workflow when patterns appear
  • Adjust fields or instructions if needed
Accuracy improves through human feedback loops.

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When to refine the workflow

You should consider refining a workflow when:
  • The same field is often corrected
  • Accuracy plateaus below expectations
  • New document variations appear
Refinement improves future documents, not past ones.

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A realistic quality goal

You don’t need:
  • 100% confidence
  • 100% accuracy
A good goal is:
High accuracy with focused human review on low-confidence cases.
That’s how anyformat scales without burning time.

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How Analytics fits into the bigger picture

Verification tells you what is correct now. Analytics tells you how good the system is overall. Together, they help you:
  • Decide where to spend time
  • Decide when to scale
  • Decide when a workflow is “good enough”

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What’s next?

Fields & instructions

Improve field definitions and instructions to raise accuracy

Recipes

End-to-end examples for common document types