Classification & extraction
Identify document types and extract agreed fields using suitable OCR, language or vision models. Preserve links to the original document so staff can check the evidence.
Build / From a PDF to the next action
Intelligent document processing.
Automate document classification, extraction and validation, then send reviewed data to the right business system. We build the complete workflow around invoices, forms, contracts and other recurring documents.
Discuss this with usThe opportunity
Turn incoming documents into usable data.
Your team retypes fields, checks totals and searches for missing details. Documents arrive in different formats, and errors often become visible only after information has already been entered into another system.
Choose a document type and destination first. We assemble representative samples, define the required fields and validation rules, and build a review route for exceptions. Extraction quality is assessed field by field and against the downstream task.
What we can do.
Validation & exception review
Check required values, formats, totals and business rules. Surface missing information, duplicates and conflicting fields in a reviewable queue.
System integration
Write approved records to your accounting, operations or case-management software. Include duplicate protection, status tracking and recoverable failures.
Tangible outputs
What you receive.
The exact scope is agreed around your workflow. A typical engagement can include:
- A document and field specification
- An extraction and classification pipeline
- A review interface or integrated review queue
- Validation rules and destination-system integration
- Field-level quality and exception reporting
Illustrative workflow
An invoice arrives by email
Identify the supplier → extract fields → check totals and duplicates → review exceptions → create the approved record.
An example of how this capability can fit a business process.Define what better looks like.
We agree useful measures before implementation and compare them with the current workflow.
- ↗Field-level accuracy and exception volume
- ↗Review time per document
- ↗Correct records created without duplication
Your questions, answered.
Can you process scanned documents?
Potentially. Scan quality, handwriting, layout and the required fields affect the approach. Representative samples are needed to assess feasibility.
Can every document be processed automatically?
Some may need review or manual handling. The aim is an effective overall workflow with visible exceptions, rather than assuming every input is suitable for straight-through processing.
Can this integrate with our finance system?
We assess the system interface and posting rules. Extraction and record creation are separate steps, and approvals can remain part of the process.
Useful before you start
Questions worth exploring.
Document automation without losing control
Extraction is one step. Reliable document processing also needs validation, review, integration and a record of what happened.
How to choose your first AI project
Start with work you can observe, data you can access and an outcome you can measure.
From AI pilot to production: what changes?
A working demonstration is a starting point. A released service also needs integration, ownership and a dependable response to failure.
A useful next step
Bring us the work
that should work better.
One process, one product idea, or a question about where to start.