Intelligent document processing that sends only the exceptions to people
Invoices, contracts, applications, claims and lab reports are read, checked against your own records and entered into your systems. Your team reviews only what doesn’t add up.
- Vendor
- Northshore Supply
- Invoice
- INV-20931
- PO number
- 4471
- Total
- $18,240.00
- From kickoff to your first document type in production
- 4–6 weeksFrom kickoff to your first document type in production
- Scored for confidence and linked to where it sits on the page
- Every fieldScored for confidence and linked to where it sits on the page
- Processed in Canadian cloud regions, in your account
- In CanadaProcessed in Canadian cloud regions, in your account
Your data arrives as paper, and someone types it in.
Suppliers send PDFs, customers send scans, partners send spreadsheets, and every one is laid out differently. So skilled people spend their days reading documents and re-keying numbers, and errors surface weeks later in a reconciliation. Intelligent document processing reads the document the way a trained clerk would, checks it, and only asks a person when something is off.
- AP staff key in hundreds of invoice lines a week, then chase the mismatches
- Template-based OCR breaks every time a supplier changes its layout
- Claim and application files wait in a queue because someone has to read them first
- Key contract dates and terms live only inside PDFs nobody can search
How intelligent document processing works, step by step
Each document goes through the same pipeline: classify it, extract the fields and tables you need, validate them against your own data and rules, then post the clean result to your system. Anything uncertain or out of policy lands in a review screen with the source highlighted, and each correction makes the next run better.
Reads any layout
Native PDFs, scans, phone photos, email bodies and attachments, in English and French, with no per-supplier templates to maintain.
Extracts fields and tables
Header fields, line items, signatures, check boxes and handwritten values where legible, returned as structured data you define.
Validates against your records
Totals must add up, vendors must exist, POs must match, policy limits must hold. Checks run against your ERP and master data, not just the page.
A review screen for exceptions
Reviewers see the document beside the extracted data, with uncertain fields highlighted on the page, and approve or correct in seconds.
Posts to your systems
Clean data goes to NetSuite, SAP, Dynamics, Guidewire, your claims or lab system, or a database, with the original document attached.
Measured on your documents
Field-level accuracy is tracked against a test set of your real documents, and every correction becomes a new test case.
Documents worth automating first
Supplier invoices and receipts
Line items are extracted, matched to POs and receipts, coded to GL accounts and posted. Price and quantity variances go to a reviewer.
For: Finance and accounts payable
Contracts and amendments
Parties, terms, renewal and notice dates, liability caps and pricing clauses pulled into a searchable register with reminders.
For: Legal, procurement and sales operations
Applications and onboarding files
Loan, account, permit or benefits applications checked for completeness, with missing items requested before a person picks up the file.
For: Financial services and public sector
Insurance claims packages
Claim forms, estimates, invoices and medical or repair reports are split, classified and summarized for the adjuster.
For: Insurance claims
Lab, quality and inspection reports
Results, specifications and sign-offs extracted from certificates of analysis and inspection reports, with out-of-spec values flagged.
For: Pharma, life sciences and manufacturing
Shipping and customs documents
Bills of lading, packing lists and commercial invoices captured and reconciled against the order before goods arrive.
For: Logistics and distribution
How we put a document type into production
- 01Week 1
Collect samples and define fields
We gather a few hundred real documents, agree on the fields and rules that matter, and record how your team handles exceptions today.
- 02Week 2–3
Prove accuracy on your documents
Extraction runs on your samples and we report field-level accuracy against hand-checked answers, before anything is connected.
- 03Week 4–5
Validate, review and integrate
We add validation against your systems, the review screen, posting to your ERP or line-of-business system, and logging.
- 04Week 6 onward
Go live and widen
Volume ramps up with full review at first, then only exceptions. We add the next document type once the first is stable.
What you get
- A document pipeline running in your cloud
- Inbound capture from email, upload, SFTP or scanner
- Review screen for exceptions and corrections
- Validation rules tied to your systems of record
- Integration with your ERP, claims or lab system
- Test set and field-level accuracy report
- Privacy impact assessment under PIPEDA and Law 25
- Monthly volume, accuracy and exception report
What it’s built with
- Models
- ClaudeGPTGeminiMistral OCRAzure Document IntelligenceAWS Textract
- Systems we connect to
- NetSuiteSAPDynamics 365GuidewireSharePointSalesforce
- Infrastructure
- AWSAzureGoogle CloudDurable workflowsPostgresObject storage
Frequently asked questions
Send us 20 sample documents. We’ll show you the extracted data.
Pick the document type your team keys in most. In a free 30-minute call we’ll look at samples, tell you what can be automated and what a first phase would take.
30 minutes with a senior engineer. No sales pitch, no obligation.
