For the documents nobody has time to key in by hand
Intelligent Document Processing
Unstructured documents, invoices, contracts, forms and claims, are where operations teams lose hours to manual data entry every week. This practice builds extraction that turns those documents into structured data automatically, with a confidence threshold deciding what a person still needs to check. The review gate is not an afterthought; it is the reason the output can be trusted downstream.
Where the review gate gets set
Confidence thresholds, format variety and integration into the system that receives the data.
90 secSample frame · video pending01Before extracting a single field
The real decision is where the review gate sits.
Every document workflow tempts a team to automate everything at once. Four questions decide how wide the human-review gate needs to stay at launch.
How costly is a wrong extraction here?
A wrong invoice line item is cheap to catch. A wrong contract obligation or claims field can be expensive, so the threshold tightens accordingly.
How consistent are the document formats?
Invoices from a handful of known vendors extract more reliably than free-form contracts or handwritten claims forms with no fixed layout.
What does the downstream system actually require?
Extraction has to match the exact fields and format the ERP or claims system expects, not a generic data structure.
Who reviews what falls below the threshold?
A review queue nobody owns just becomes a backlog. The reviewer and their turnaround time get named before launch.
| Manual entry | OCR alone | Governed extraction | |
|---|---|---|---|
| Speed | Slowest | Fast, but unchecked | Fast, with a review gate |
| Accuracy on messy documents | Depends on the person | Drops sharply | Holds, because uncertainty routes to a person |
| Downstream integration | Manual re-keying | Still needs mapping | Built directly into the extraction |
| Audit trail | Inconsistent | Rarely captured | Confidence scored per field |
02Agreed before the threshold is set
The ledger that keeps extraction honest
Document processing engagements break down when the confidence threshold gets set once and never revisited. This ledger fixes what you bring, what gets extracted, what returns to you, and what stays a human decision regardless of confidence.
- Your side
You bring
- A sample of the actual invoices, in their real formats
- The ERP or accounting system the data needs to reach
- Current error rates and where mistakes typically slip through
- Our side
We build
- OCR and extraction tuned to your actual invoice formats
- A confidence threshold routing uncertain extractions to a person
- A direct integration into the ERP, not a spreadsheet export
- Your side
You receive
- Structured invoice data landing in the ERP automatically
- A review queue for exactly the extractions worth checking
- Error rates tracked against the old manual process
Never leaves you
- The chart of accounts and every approval rule
- Final sign-off on payments regardless of extraction confidence
- The right to route any vendor's invoices to manual review
Where the line sitsAutomating invoice entry does not automate approval. Money still moves only when a person your process names says so.
03From real documents to a trusted queue
Four stages, each closing on evidence
Deployments that lose trust usually skipped a stage here. This system closes each one with something your team can verify before coverage ever widens.
Study the real documents, not a sample template
Actual invoices, contracts or claims are reviewed for format variety and the fields that genuinely matter to the business.
Formats studied before extraction is tunedSet the confidence threshold and the review gate
The line between automatic extraction and human review is set from how costly a wrong answer would be in your workflow.
A threshold set from your own risk toleranceLaunch on a limited document set
Extraction goes live on the clearest, most common formats first, with review turnaround measured from week one.
A narrow launch against real volumeExpand coverage as accuracy earns it
Additional document types and formats are added only once extraction accuracy on the first set is proven in production.
Coverage widens on measured accuracy
04What actually moves the number
Four drivers, priced from your documents
Pricing follows document volume and format variety, not a flat licence fee. These four factors change the number most.
Volume and variety of document formats
A single, consistent document type costs less to automate than a mix of scanned, handwritten and digital formats.
Required extraction accuracy and review depth
Contracts and claims touching compliance need tighter thresholds and more review capacity than routine invoice processing.
Integration depth with the downstream system
A downstream ERP or claims system with a documented interface integrates faster than a legacy system with no clean way in.
Volume of documents processed per period
A steady, moderate volume costs less to build for than a system that must absorb sharp seasonal spikes.
05Evidence and proof
Extraction that earned the trust of the review queue.
Proof here is an accuracy rate that held and a review queue sized to what it actually needed. These previews carry that standard while written client approvals are collected.
Explore case studiesInvoice keying removed without removing anyone's approval authority.
Nexa Foundry keyed hundreds of supplier invoices by hand each week. Extraction into the ERP freed the team while every payment still required the same named sign-off.
- Invoices auto-extracted
- Majority of volume
- Approval process
- Unchanged
Claims routed into a case system without manual re-keying.
Koru Health received scanned claims that a team retyped into their case management system by hand. Structured extraction mapped directly to the system's required fields.
- Manual re-keying
- Eliminated
- Ambiguous claims flagged for review
- Clearly separated from clean ones
It tells us what it is unsure about instead of guessing, which is the whole reason we trust it.
Sample · pending client approval
06Read this first
When document extraction is the wrong move
Automating extraction before document volume or error cost justifies it wastes budget better spent elsewhere. The exits are marked plainly. When the work is justified, it integrates with your existing ERP, claims or case management system directly.
Document volume is genuinely low
A handful of documents a week rarely justifies a dedicated extraction system; existing manual review may already be fine.
Every document requires case-by-case judgment
If interpreting each document is inherently a judgment call, extraction has little safe to automate yet.
- Team extension
You need data-entry capacity, not automation
If the actual gap is temporary volume during a growth spurt, extending the team fits better than building a system.
| Shape | Best when | You direct | We carry |
|---|---|---|---|
| Scoped deployment | Document types and fields are known | Scope and review cadence | Extraction, thresholds and delivery |
| Phased rollout | Multiple document types need staging | Rollout order by document type | Tuning and monitoring per type |
| Team extension | Your team owns the AI strategy | Architecture and standards | Named engineers and continuity |
07Straight answers
Asked before extraction touches real documents.
01How accurate is the extraction?
Accuracy depends on document consistency and how tightly the confidence threshold is set. Anything below that threshold routes to a person rather than getting guessed at.
02What document types can this handle?
Invoices, contracts, forms and claims in scanned, handwritten or digital formats. Extraction is tuned to your actual documents, not a generic template.
03Who reviews the extractions marked uncertain?
A named reviewer on your team, with a turnaround time agreed before launch. An unowned review queue just becomes a backlog nobody clears.
04Can it integrate with our ERP or claims system?
Yes, extraction is mapped to the exact fields and format your downstream system requires. Manual re-keying between systems is what this removes.
05What happens with a document format we did not anticipate?
It routes to review by default rather than getting forced through extraction. Coverage expands to new formats only once accuracy on them is proven.
06Is this suitable for sensitive or regulated documents?
Data handling is scoped to your existing compliance requirements during the assessment. Sensitive fields can carry stricter review thresholds than routine ones.
07What does this cost?
Pricing follows document volume, format variety and how much review depth compliance requires. A single, consistent document type costs less than a varied mix.
08How long before it is processing real documents?
A narrow launch on the clearest format typically takes weeks. Broader coverage across formats is staged and paced by measured accuracy.