INTELLIGENT DOCUMENT PROCESSING
Document processing and structured data extraction
We build intelligent document processing that reads, extracts and validates information, with human review for exceptions and uncertain results.
- Confidence scoring on every field, so automation is gated safely
- A review queue where humans resolve only the exception fields
- Validated output posted straight into your systems of record
A sequence of stages, each measurable and tunable.
The design of these stages determines how much work actually gets automated.
We lead with the pipeline because that is where the automation line is drawn. Intelligent document processing is one of our applied AI solutions and shares its extraction core with Structured Data Extraction. Pair the output with an approved downstream workflow to action it.
Ingest and classify
Accept documents from email, upload, or scan, and identify each type so the right extraction logic applies. The right document meets the right pipeline.
OCR and layout
Read text and understand structure: tables, key-value pairs, and signatures, not just flat characters. Structure, not just text.
Extract
Pull the fields that matter using LLM and vision-language models that read messy, variable layouts. Variable layouts, not rigid templates.
Validate
Check extractions against business rules, reference data, and cross-field logic; score every field. A confidence score on every field.
Route
Send high-confidence documents straight through; queue low-confidence or exception fields for review. Straight through where it is safe.
Learn
Feed human corrections back, so accuracy improves on the documents you actually see. Corrections become training signal.
High-confidence documents flow straight through, only the exceptions reach your team.
Extraction, gating, and a review path that keeps automation safe.
- Document classification and extraction tuned to your document types.
- Confidence scoring and validation rules that gate automation safely.
- A review queue where humans resolve only exception fields, not whole documents.
- Integration that posts structured output into your systems of record.
- A feedback loop that turns corrections into a rising straight-through rate over time.
Straight-through processing, or a human in the loop.
The most important decision in any deployment is where to draw the line. Set it too aggressively and errors slip through; too conservatively and you have automated nothing. We set the threshold per document type and field, aggressive where a mistake is cheap, conservative where it is not.
Reviewers do not re-key whole documents; they resolve only the flagged fields, so human effort concentrates where it adds value.
Five steps, from a pile of documents to straight-through flow.
Classify the mix
Map your document types and volumes, and the fields each one has to yield.
Set the line
Agree the confidence threshold per document type and field from your risk appetite.
Build and validate
Extraction and validation tested against a labelled sample from your real long tail.
Integrate
Post structured output into your systems of record, where work already happens.
Close the loop
Reviewer corrections lift the straight-through rate on the documents you see most.
Established OCR engines, LLM and vision extraction, on your platform.
A representative stack by layer. We use your existing tooling where it is sound rather than replacing it.
We will not quote you a headline accuracy number. On well-structured documents, field-level accuracy is genuinely high; on the messy long tail, poor scans, handwriting, unusual layouts, it is lower, which is exactly why the review queue exists. We measure field-level accuracy and straight-through-processing rate against a defined baseline, in production. We measure the right metric per use case, not a vanity number. Data handling aligns to Responsible AI and Governance.
Part of a portfolio built to an accuracy bar.
Structured Data Extraction
The extraction engine underneath IDP, pointed at forms, PDFs, email, and scans.
Enterprise Knowledge Assistant
RAG over your content with citations, once documents are structured and searchable.
Fraud Detection
Precision and recall tuned to expected loss, another workflow engineered to its metric.
GenAI Email Categorization and Automation
Classify and draft on inbound queues, the same confidence-gated pattern for email.
IDP Accelerator
A defined eight-week path to a measured document workflow with exception handling and operational controls.
Generative AI Solutions
The parent portfolio this solution belongs to, each engineered to an accuracy bar.
What teams ask us first.
High on structured documents, lower on the messy long tail, which is why confidence gating and a human review queue are built in. We measure field-level accuracy and straight-through-processing rate against your baseline in production, not a demo figure.
Yes. Classification routes each document to the right extraction logic, and LLM and vision-language models handle variable layouts rather than requiring a rigid template per format.
Straight into your systems of record. The goal is validated data where work already happens, not another screen your team has to check.
Tell us the document type costing you the most time, we will show the straight-through rate it can reach.
And where the human line should sit, so automation carries the routine load while your team keeps the exceptions.