Operations teams don't have a document problem; they have a thousand small ones. Invoices arriving by email, IDs as phone photos, contracts in portals, statements as scans of prints of faxes. Each one needs reading, typing, checking, filing. Multiply by volume and entire departments exist to move information from paper-shaped things into systems.
Why OCR didn't finish the job
Classic OCR turns pixels into characters. It doesn't know an invoice from a passport, a due date from a birth date, or whether the total it read is plausible. Every OCR deployment grew a hedge of templates and regexes that broke whenever a supplier redesigned their invoice. The technology digitised documents without understanding them.
The modern pipeline
Intelligent document processing (IDP) treats the problem as a pipeline with checkpoints — the architecture behind Capture672:
1. Ingest
Every channel — email, scan, upload, portal — lands in one queue. Format and quality stop mattering at the front door, because the pipeline normalises everything behind it.
2. Extract and classify
Models recognise document types and pull fields and tables without templates, reading layout and language together the way a person does. Every extracted value carries a confidence score — the load-bearing feature of the whole system.
3. Validate
Extraction is checked against systems of record: does the PO exist, does the VAT number resolve, do the line items sum? Matches flow straight through. Mismatches and low-confidence values route to a human reviewer whose correction retrains the models.
4. Index
Everything processed becomes searchable by meaning, not just keywords. The archive stops being storage and starts being an answer: "show me every contract with an uncapped indemnity" is a query, not a quarter-long project.
Confidence thresholds are how 99% automation stays safe: the system knows what it knows, and asks about the rest.
What "99% less manual" means in practice
It does not mean 99% of documents are untouched by humans on day one. It means the review queue converges there: as corrections retrain extraction on your document estate, straight-through rates climb from typical starting points of 60–80% toward the high nineties, and human attention concentrates on the exceptions that genuinely need judgement. Accuracy compounds with volume — a property template-based systems never had.
Buying criteria that matter
- Confidence scoring and human-in-the-loop review, not blind straight-through processing.
- Validation against your systems of record, not just extraction accuracy benchmarks.
- Learning from corrections in your environment.
- Semantic search over the processed corpus — the compounding asset most buyers forget to ask about.
Documents are where operations slow down. They're also the fastest automation win most organisations are sitting on. Ask us how fast.