Prove the accuracy on one document type before scaling to others.
The scale decision should rest on measured accuracy, not impression. Running a controlled pilot on one document type gives a real number — how often extraction is right first time, and how much review time it saves.
You select a representative batch, process it through Nanonets, verify every extraction against the original, and record first-time field accuracy and the review time versus the fully manual check. The pilot result is both numbers: accuracy and time saved.
Turn the pilot into an evidence-based decision on whether to scale.
Get the extracted data into the systems Registry actually works in.
Manage the $200 free credits so the pilot runs without a surprise bill.
Select a representative batch of the pilot document type.
Process the batch through Nanonets.
Have an officer verify every extraction against the original.
Record how many fields were correct first time.
Measure the review time against the previous fully manual check.
Report the accuracy and time saving as the pilot result.
Batch: [number] documents Fields per document: [number] Total fields: [number] After verification: - Correct first time: [number] fields - Accuracy: [number] ÷ [number] = [percentage]% Timing: - Manual check (baseline): [number] minutes per document - Nanonets + review: [number] minutes per document - Time saved: [number] minutes per document ([percentage]% reduction) Pilot result: Document type: [type] Accuracy: [percentage]% Time saving: [percentage]% ([number] minutes per document)
Process a representative batch, have every extraction verified against the original, record first-time field accuracy and the review time versus the fully manual check, and report both.
Cross-check extracted values against what Registry already holds.
Teach Nanonets the exact fields Registry needs from one document type.