Turn document queues into checked, structured data your systems can use.
Invoices, claims, applications, contracts and forms are read, classified and extracted automatically, checked against your systems of record, and routed — with a person reviewing anything the system is unsure about.
- 01Intake
- 02Classify and extract
- 03Check against records
- 04Review exceptions
- 05Route and post
The workflow
Operations, finance and compliance teams who open, read and re-key documents into other systems every day.
- Documents arrive by email, upload and scan in dozens of layouts.
- People re-type the same fields into two or three systems.
- Errors are found late, often by a customer or an auditor.
- Nobody can say how long a document waits before it is processed.
Intake
SystemDocuments are collected from inboxes, upload portals and shared drives into one queue.
Classify and extract
AIThe model identifies the document type and pulls out the fields that matter, with a confidence score for each.
Check against records
SystemExtracted values are compared with the ERP, CRM or policy system — totals, names, dates, reference numbers.
Review exceptions
PersonAnything below the confidence threshold or failing a check is shown to a reviewer with the source highlighted.
Route and post
SystemApproved data is written to the target system and the document is filed with an audit trail.
Where people stay in control
Reviewers see every low-confidence field and every failed check, with the source document beside it. Thresholds are tuned per field, and nothing is posted to a financial system without passing its checks or a person's approval.
- Share of documents processed without manual edits
- Field-level accuracy on a held-out sample
- Time from arrival to posting
- Reviewer time per document
Data and integrations
- Sample documents covering the main layouts
- Access to the systems of record used for checks
- Target system API or import format
- Current validation rules
Realistic boundaries
- Handwritten and badly scanned documents usually need more review.
- Accuracy is measured per field on your documents — we don't quote a general figure.
- Legal or medical judgement stays with qualified people.
How we build it
- Generative AI & LLM DevelopmentApplications built on large language models that are grounded in your data, tested against real cases and costed before launch.
- AI AgentsAgents that take approved actions across your tools, with permissions, review points and monitoring built in.
- Data EngineeringData architecture, pipelines, quality and access that make your data usable for reporting, operations and AI.
- AI IntegrationConnect AI models and assistants to your CRM, ERP, databases, knowledge stores and APIs — with identity, logging and fallbacks that production systems need.
- Financial ServicesDocument review, knowledge access, fraud signals and customer operations — built with the controls and auditability the sector expects.
- InsuranceClaims intake, underwriting submissions, policy knowledge and fraud signals — AI that prepares the file so adjusters and underwriters decide with the evidence in front of them.
- Logistics & Supply ChainShipping documents, exception handling, planning and visibility across carriers, warehouses and partner systems that were never designed to talk to each other.
- Healthcare & Life SciencesAdministrative documents, prior authorizations, knowledge access and regulated content workflows — built for privacy, clinical oversight and careful claim boundaries.
Questions buyers ask
OCR turns an image into text. Document intelligence understands what the text is — which number is the total, which date is the due date — checks it against your records, and decides where it goes.
Modern models handle new layouts without templates. We confirm this on your own samples during discovery and report field-level accuracy before anything goes live.
Map this workflow with us.
Tell us about the workflow or product. We reply with questions, a suggested first step and who would work on it.