FAQ
How accurate is OrderPilot, really?
Our honest accuracy numbers broken down by field and document type, plus the feedback loop that gets you from 95 % to 99.5 % in the first month.
OrderPilot averages 99.2 % field-level accuracy across our customer base - but that number hides useful detail. Here’s what actually happens.
Day one accuracy
On the first PO from a brand-new supplier with no prior template, expect:
- Header fields (supplier, PO number, date, total): ~97 %
- Standard line-item fields (qty, unit price, line total): ~94 %
- Edge-case fields (UoM, delivery address, payment terms): ~88 %
These numbers come from our confidence-calibrated extraction, not marketing.
After 30 days (with corrections)
By the time you’ve processed 20–50 POs from a supplier, the model has learned that supplier’s template, terminology, and corrections. For established suppliers we see:
- Header fields: 99.8 %
- Line items: 99.2 %
- Edge fields: 97.5 %
What drives accuracy
Three things, in order:
- Supplier template consistency - if a supplier sends the same format every time, we nail it
- Your correction feedback - every correction you make in OrderPilot improves extractions from that supplier
- SKU and vendor master completeness - without good reference data, we have nothing to match against
What doesn’t drive accuracy
Common things customers worry about that mostly don’t matter:
- Scan quality - our OCR handles low-res scans down to ~150 DPI
- Handwritten notes - these are always flagged for manual review (by design)
- Multi-page POs - handled natively, no config needed
- Non-standard formats - we learn per-supplier, so unusual formats are fine as long as they’re consistent
The 100 % claim on the homepage
The “100% accuracy” headline refers to downstream document-level accuracy after validation queue review: no PO enters your ERP with an uncorrected error. It’s a claim about process, not raw extraction.
If you want the raw extraction numbers for diligence, ask for our statistical accuracy report during onboarding.
Related articles
- Tips & Best Practices99.9% accuracy explained: how we measure it and why it mattersAn engineering post on what 99.9% accuracy actually means — which fields, which document types, which correctable with human-in-the-loop, and how we measure it continuously. Read
- Tips & Best PracticesReducing PO errors systematically - a 4-week playbookTeams that cut PO error rate from 3 % to under 0.5 % in one month follow this exact sequence. Each week builds on the last and the work is small but non-negotiable. Read