Aurum Quanta IDP.
Forms, invoices, statements, and PDFs read and routed without human retyping.
If a person on your team is keying invoice data into the ERP by hand, this is the service. Forms, invoices, contracts, statements, scanned PDFs: read, classified, and routed automatically, with a reviewer queue for the cases the model isn't sure about. The structured output lands directly in the ERP, CRM, or warehouse that consumes it.
OCR, layout-aware transformers, and small fine-tuned classifiers. Every prediction is logged with a hash of the source document and a confidence score, so you can reconstruct any decision the system made when an auditor asks six months later.
From document to structured data, in 3 seconds.
Drop a document
Drag a PDF, PNG, JPG, or WebP - or click to browse. Max 5 MB.
{
"document_type": ...,
"vendor": { "name": ..., "address": ... },
"date": ...,
"total": ...,
"currency": ...,
"line_items": [...],
"confidence": ...
}Drop an invoice, receipt, or quote. We'll extract vendor, date, totals, currency, and line items as structured JSON. Powered by Claude vision - the same engine we'd build into your pipeline.
From document to structured data.
Every page enters at ingest, gets layout-aware extraction, is scored for confidence, and routes to auto-pass, human review, or escalation. Same shape, different documents.
Concrete deliverables.
Layout-aware extraction
Tables, key-value pairs, signatures, handwritten fields. Transformer-based models handle variable layouts without the brittle template-matching that older OCR pipelines relied on.
Confidence scoring
Every extracted field carries a reliability score. High-confidence fields pass straight through. Low-confidence fields wait in a reviewer queue until a human signs them off.
Human-in-the-loop review
A reviewer UI built for the edge cases the model can't handle alone. Corrections feed back into a quarterly retraining cycle so the model gets quietly better at the things it used to escalate.
API and ERP connectors
Structured output lands in SAP, NetSuite, Xero, Salesforce, your data warehouse, or a custom endpoint we wire up.
Low-confidence fields go to review, not into your system of record.
# extract/invoice.py: typed extraction, route weak fields to human review
def extract(doc: bytes, threshold: float = 0.85) -> Extraction[Invoice]:
fields = ocr_then_classify(doc)
needs_review = {k: v for k, v in fields.items() if v.confidence < threshold}
if needs_review:
return Extraction(value=None, review=needs_review)
return Extraction(value=Invoice.model_validate({k: v.value for k, v in fields.items()}))Pydantic schema + per-field confidence. Nothing enters production half-known.
How it would unfold.
Audit
Document sample review, field definition, target accuracy per field agreed.
Pilot
Extraction pipeline on a representative set, measured against manual baseline, tuned to your confidence thresholds.
Production
ERP or API integration, reviewer UI, monitoring, retraining pipeline for edge cases.
Ongoing
Quarterly accuracy review and retraining on newly-seen edge cases.
Tools we reach for on this kind of work.
Common questions.
What accuracy can we expect?
It depends almost entirely on document quality. Modern layout-aware OCR and transformer-based extractors achieve 85–98% per-field accuracy on clean scans after tuning, based on published benchmarks. The range is wide enough to be useless as a commitment, so we benchmark on your actual documents in week 2 before quoting a number.
Can it handle handwritten forms?
Most of the time, yes. Modern OCR and transformer models handle most consumer handwriting reasonably well; cursive and faxed remittance advice are harder. We'll test on your samples and tell you which categories are going to need permanent human review.
Does it replace all manual review?
No, and we'd push back if you wanted it to. High-value documents (six-figure invoices, contracts with unusual terms) should keep a human reviewer by design. What IDP removes is the mechanical retyping; the judgement calls are still yours to make.
Let's build it.
A 30-minute discovery call. We'll tell you whether we're the right shop for this.
Book a discovery call →