Document AI OCR Pilot Checklist (Free)

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18 critical items still open - these are the highest-risk gaps.

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Scope and success criteria

Document types in scope are listed (supplier invoice, credit note, certificate of conformance, packing slip)CRITICALOut-of-scope documents are named so they are not counted as failuresThe business owner who signs off on the pilot result is namedCRITICALBaseline is measured: current handling time per document, error rate and rework rateCRITICALSuccess thresholds are written down before the pilot starts (field accuracy, straight-through rate, cost per document)CRITICALPilot duration and the decision date are fixedFallback plan exists if the pilot is stopped

Sample set and ground truth

Sample set is drawn from real production documents, not clean examplesCRITICALSample covers all major suppliers and also a long tail of small suppliersPoor scans, photos, faxes and rotated pages are included on purposeCRITICALAt least a few hundred documents per type are available for testingEach document has a verified ground truth for every field to be extractedCRITICALTwo people label a subset so that disagreement rate is knownTest set is kept separate from any documents used to tune rules or promptsCRITICALLanguages and character sets are listed (accents, non-Latin scripts)

Metrics and review process

Field-level accuracy is measured per field, not as one blended numberCRITICALPrecision, recall and F1 are computed where fields may be missingStraight-through rate is measured as documents posted without a human touchCRITICALConfidence threshold is chosen from measured data, not by guessHuman review step and queue owner are definedCRITICALTime per reviewed document is recordedErrors are categorized (image quality, layout, engine, validation rule)

Validation and ERP integration

Vendor master match is part of the flowCRITICALDuplicate invoice detection is defined (supplier plus number plus amount plus date)CRITICALThree way match tolerances are agreed (price, quantity, tax)Document type routing is defined for credit notes, proformas and corrected invoicesPosting method is chosen (park document, workflow, direct post)CRITICALTest environment of the ERP is available with representative master dataCRITICALAudit trail keeps the source image, the extracted values and who changed themAttachment storage in the ERP or archive is decided

Security, privacy and operations

Data classification of the documents is confirmed (export-controlled, customer confidential, personal data)CRITICALWhere documents are processed and stored is decided and approvedCRITICALRetention and deletion rules apply to the pilot copiesAccess to the pilot environment is limited and loggedVendor contract states what happens to submitted documents and whether they are used for trainingCRITICALEmail inbox or scan source feeding the pilot is definedSupport contact and incident process are in place for the pilot period

Do not start the pilot until every critical item is checked. Unchecked non-critical items should have an owner and a date.

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How to use the checklist

Work through the groups with the AP lead, quality lead and IT. Tick items as they are done and use the export to share the status. Critical items are those that make the result untrustworthy if missing, such as a ground-truth set or a pre-agreed threshold. Treat the checklist as a gate: when all critical items are complete, you can compare tools on equal terms.

Why ground truth comes first

You cannot measure accuracy without a verified answer for every field. Building ground truth is slow, but it is the asset that lets you compare vendors, tune confidence thresholds and detect regression later. Use a double-labeled subset to find out how often humans disagree, because that rate is the ceiling for any automated result.

Label real documents, including the bad ones
Keep a separate untouched test set
Measure per field and per supplier
Record the document source and scan quality

Metrics that matter

A single accuracy number hides the problem. Report field-level accuracy, the straight-through rate and the cost of review. A system that reads 98 percent of characters correctly can still post wrong amounts if the errors concentrate in the total field. Pick the confidence threshold by plotting accuracy against the share of documents auto-accepted, and choose the point your business can accept.

Common mistakes

Teams run the pilot on clean PDFs from the biggest five suppliers and then meet scanned, skewed and photographed documents in production. Others judge the tool by demo runs rather than by a held-out test set. A third mistake is ignoring the review process: if reviewers need three screens and two minutes per document, savings vanish.

Frequently Asked Questions

How many documents do I need for a document AI pilot?

A few hundred per document type is a practical minimum for field-level metrics, with more for rarer fields. Include enough supplier variety and poor-quality scans, since representative variety matters more than raw volume.

What is ground truth in OCR testing?

It is the verified correct value of every field for each test document, usually entered or checked by a person. Extraction output is scored against it to measure accuracy, precision and recall.

What should the straight-through rate target be?

It depends on document mix and risk tolerance, so set it from your baseline and the measured accuracy curve rather than from a vendor claim. Many teams start with a conservative threshold and raise it as evidence accumulates.

Can I pilot without sending documents outside my network?

Yes. Open-source OCR and open-weight models can run on your own servers. Decide this early, because it affects tool choice, hardware needs and the approval path for documents with export-controlled or confidential content.

If you want help preparing a pilot and running it privately on your own infrastructure, Netray can support the setup and measurement.

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