Documents in, structured data out
Invoices, contracts, applications, forms, processed automatically. Extract fields, classify documents, route to the right workflow. Zero manual keying.
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Document types we process
Processing pipelines we have built for clients in the past two years, across finance, legal, HR, and operations.
Invoices
Vendor name, amount, line items, VAT, due date — extracted and pushed to your ERP or accounting system. Edge cases flagged for human review rather than silently misread. Typical accuracy on clean PDFs: 95–99%.
- Vendor, amount, line items, VAT, due date extracted — field coverage defined by your ERP or accounting system requirements
- 95%+ accuracy on trained document types — benchmarked on your actual invoice sample before go-live
- Exceptions flagged for human review — system does not guess when confidence is low, it queues for someone to check
- Pushed directly to ERP or accounting system — SAP, Oracle, QuickBooks, Xero, or custom via API
Contracts
Parties, dates, key obligations, penalty clauses extracted automatically. Non-standard terms flagged before the document reaches legal. Summary generated in plain language. Saves hours of manual review per contract.
- Parties, dates, key obligations, penalty clauses — extracted and structured into a consistent format every time
- Non-standard terms highlighted before legal review — unusual clauses surface before the document reaches a human reviewer
- Plain-language summary generated automatically — executive summary alongside the structured data for quick decision-making
- Supports your legal review workflow — integrates with DocuSign, SharePoint, or your document management system
Application forms
Intake forms, loan applications, onboarding packets. Fields extracted, validated against your business rules, and routed to the right team or system. Works for structured forms and variable-layout documents alike.
- Intake forms, loan applications, onboarding packets — structured layouts and variable-format documents both handled
- Field validation against your business rules — missing fields, out-of-range values, and inconsistencies flagged
- Routing to correct team or system — application type determines destination automatically
- Handles handwritten fields where quality permits — falls back to review queue for illegible content rather than guessing
Incoming email
Emails classified by intent and type, key data pulled out, tickets or CRM records created automatically. Works with your existing Gmail or Outlook inbox without changing how people send things.
- Classified by intent, type, and priority — support request, invoice, complaint, and enquiry handled differently
- Tickets or CRM records created automatically — Zendesk, Freshdesk, HubSpot, Salesforce, or custom system
- Works with your existing Gmail or Outlook inbox — no change to how senders send, no inbox restructuring
- Human review queue for low-confidence classification — uncertain cases surface for review instead of being misrouted
Compliance documents
KYC documents, certificates, licenses, regulatory filings. Fields verified, expiry dates tracked, results stored in structured format ready for audit. Reduces the manual compliance review workload by 60–80%.
- KYC documents, certificates, licenses, regulatory filings — fields verified, document type classified, validity checked
- Expiry dates tracked with automated alerts — notification sent before a certificate lapses, not after
- Structured output ready for audit — every extraction logged with source document reference and timestamp
- GDPR-compliant pipeline options — on-premise or private cloud deployment for sensitive compliance data
Reports and statements
Tables extracted from PDFs and scanned documents, data consolidated across multiple reports, output to CSV or pushed directly to your data warehouse or BI tool. Handles irregular table formats and multi-page documents.
- Tables extracted from PDFs and scanned documents — multi-page tables, merged cells, and irregular layouts handled
- Data consolidated across multiple reports — same metric across 20 weekly reports merged into one clean dataset
- Output to CSV or data warehouse — Snowflake, BigQuery, Redshift, or direct database insert
- Handles irregular table formats — trained on your specific report format, not a generic template
How document processing is built
- 01
Document audit
We collect samples across all the document types you handle. Map the fields, find the edge cases, identify which variants will cause problems.
- 02
Pipeline design
OCR layer, extraction model, validation logic, exception routing. We pick the right tool for each step rather than applying one approach to everything.
- 03
Build and calibrate
Pipeline built against your real documents. Accuracy benchmarked before anything goes near production.
- 04
Connect and deploy
Hooks into your inbox, file storage, ERP, or custom API. Human review queue catches anything below the confidence threshold.
- 05
Monitor
Extraction accuracy tracked over time. When new document variants start appearing, we catch the drift before it becomes a problem.
Common questions
What accuracy should we expect?
For clean PDFs with consistent structure, 95–99% field accuracy is realistic. For poor scans or highly variable layouts, expect 85–92% with a review queue handling the rest. We benchmark before go-live so you know the numbers upfront.
Can it handle scanned documents and photos?
Yes. We layer OCR, Tesseract, AWS Textract, or Google Document AI depending on volume and quality, before the extraction step.
Does the data leave our infrastructure?
It depends on the pipeline design. For sensitive documents, we can build fully on-premise or private-cloud setups where nothing touches third-party APIs.
What format does the output come in?
Whatever you need: JSON for API consumption, CSV for spreadsheets, direct database inserts, webhook calls to your existing system.
Can it handle multiple languages?
Yes. Particularly relevant for EU companies receiving documents from across Europe. The pipeline handles language detection and multilingual extraction.
How many documents does your team process manually each month?
Give us the volume and document type — we'll tell you what's realistic to automate.
Processing documents manually?
Send us some samples and describe your current workflow. We will tell you what is automatable and what is not.
Tell us what you need to process →