OCR & data extraction
Text, figures and fields from scans, PDFs, invoices, forms and certificates — including Traditional and Simplified Chinese where needed.
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AI Document Processing
AI Document Processing & Data Extraction
From intake and OCR to classification, review and handoff — fewer copy-paste loops and clearer accountability.
We help teams automate document handling — OCR extraction, classification, validation and workflow handover — so staff spend less time on repetitive data entry and more on judgement.
- Multi-channel intake: email, uploads, forms, scans and messaging attachments into one preprocessing rhythm.
- OCR / extraction / classification before review; humans approve critical fields before ERP/CRM handoff.
- Connect to ERP, CRM, approvals or internal workflows — often one document type or queue first.
What we deliver
OCR, classification, validation and handover
Extract text and structured data; classify and route; validate against records; push to workflows without re-keying.
Document classification
Tag by type, department, urgency or content so the right workflow receives each item.
Routing rulesException queues
Validation & enrichment
Cross-check extracted data against CRM/ERP, flag mismatches, prep downstream fields.
Match & mergeException review
Workflow handover
Feed approvals, records systems or CRM without manual re-entry — status visible end-to-end.
Audit trailNotifications
Before / after
The pain is scattered intake and unclear handoffs
Processing is rarely one step — usually the problem is mixed channels, duplicate entry, inconsistent labels and chasing status in chat.
Less retypingHumans still reviewCleaner handoffs
| Stage | Typical today | With structured intake | Why it helps |
|---|---|---|---|
| Intake | Email, IM and folders — easy to miss or duplicate | Single queue with basic metadata | Fewer lost items; clearer ownership |
| OCR / extraction | Manual typing; error-prone | Draft fields for review | People check exceptions, not every character |
| Classification | Tribal knowledge | Rules plus ML-assisted tags | Consistent routing; edge cases to humans |
| Review | Informal messages | Workflow states and tasks | Traceable accountability |
| Handoff / systems | Forwarded emails | Push to ticket, ERP or CRM with status | Less “did this get entered?” chasing |
Less retypingHumans still reviewCleaner handoffs
Use cases
Common use cases
Invoice and receipt processing; application intake; contract prep; compliance packs; insurance claim documents — start where volume or error cost is highest.
Tackle the repetitive slice first
OCR and field extraction are where hours disappear — automate drafts, keep humans on judgement calls.
Pilot with one daily queue; measure accuracy and exception rates before scaling.
Keep review in the loop
Finance, contracts and personal data still get human approval — systems surface queues, not silent auto-posting.
Exceptions route to a fixed path instead of ad-hoc chats.
Fit your systems
ERP, CRM, approvals, tickets or APIs — usually start with one or two critical handoff points.
Pairs with workflow automation for end-to-end visibility.
FAQ
AI document processing — FAQ
Not always. Repetition, handoff pain and error cost matter as much as raw daily count — a single painful queue can be enough to pilot.
Rarely for regulated or financial content. The goal is to remove boring typing and clarify responsibility — not to eliminate oversight.
Yes — depth depends on APIs, permissions and data models. We usually prove one integration path, then extend.
No — contracts, applications, internal memos and certificates can be in scope when the process is describable.
Yes — cloud, dedicated environment or on-prem are discussed against policy and IT constraints; see also our private AI page.
Next step
Start with the document flow that hurts most
Pick one intake path — invoices, applications or classification — prove accuracy and handoffs, then widen. We can combine with workflow automation or private hosting as needed.