Intelligent Document Processing Consulting
Extract structured fields from contracts, invoices, and claims with citations back to the page — and a human queue when confidence drops.
- Service
- Document AI
- Industry
- Enterprise
- Updated
- 2026-08-25
- Engagement
- 4 wks
Intelligent document processing consulting helps operations teams extract structured data from contracts, invoices, and claims using layout-aware OCR plus generative filling of a versioned schema, with page-level citations, confidence-based human review, and field-level evals — typically one document type in four weeks, running in your VPC, with the client owning schemas and golden sets.
Why teams pick this engagement
Document AI × EnterpriseEvery field cites a span
Extracted amounts, dates, parties, and clauses point at a page and bounding box. A value with no locator is dropped or queued.
Layout plus generation
OCR and layout models handle scans and tables; the LLM fills a schema. Neither layer is asked to do the other’s job.
Schema is the contract
Structured generation against your JSON schema, with type checks and cross-field validators (totals, dates, currency) before a downstream system sees the payload.
Human review where it pays
Low-confidence fields, conflicting pages, and high-value documents hit a queue with the citation highlighted. Perfect automation on messy scans is not the goal.
Field-level accuracy, not “docs processed”
Precision/recall per field on a golden set of your real documents. A 99% “document success” rate that misses the indemnity cap is a failed eval.
One document type in four weeks
Invoices, a contract family, or a claims package — schema, OCR path, citations, HITL, handover — then reuse the pipeline.
Key takeaways
- 01
IDP that ships is schema-first: defined fields, types, validators, and a citation for each value — not “summarize this PDF.”
- 02
OCR and layout handle scans and tables; the LLM maps language into the schema. Using only one of those layers is how you lose line items.
- 03
A field without a page/span citation is unusable in audit and should be queued, not silently accepted.
- 04
Human review belongs on low-confidence fields and high-value documents, not on every page and not on none.
- 05
One document type in four weeks, measured per field on your golden set, beats a multi-year “ingest everything” program with no eval.
What the engagement covers
How we work
- 01
Discover
Document mix, downstream systems, field list, and the single type we will ship.
- 02
Design
Schema, validators, citation rules, HITL thresholds, and evals reviewed with ops and audit.
- 03
Build
OCR/layout, extraction, citations, and system write-back in a non-prod environment.
- 04
Validate
Field-level scores on the golden set, citation checks, and review-queue time-and-motion.
- 05
Enable
Production on that document type, runbooks, eval ownership, and 30 days on-call.
Take the playbook with you
The working documents from real engagements — free, in exchange for an email. They’re useful whether or not we ever talk.
Document Extraction Schema & Citation Spec
Field types, validators, span citations, and the confidence rules that send a value to a human instead of downstream.
Get the spec ·IDP Golden-Set Labeling Worksheet
How to sample contracts, invoices, or claims and label fields so extraction accuracy is measured the way ops actually cares.
Get the worksheet ·