Turn business documents into validated, structured data.
Not just OCR — Document Intelligence. Drop in any document — or try a sample — and we return the JSON your systems need. Self-serve gets you 80–90% on clean documents; together we tune it to >95% for the cases where a mistake actually costs you.
Enterprise-grade & private: no public LLMs are ever called, so your documents stay yours — and at high volume we'll host the whole solution inside your own cloud.
Private, enterprise AI models only.
Your documents never train anyone else.
On-prem / your VPC at high volume.
Straight into your ERP, CRM or DB.
Upload a document — get structured JSON back
Drop in any document and watch it come back as clean, structured data — the exact shape your systems would receive.
Overall on clean, consistent documents; individual machine-printed fields may exceed 90%. Measured at field level (exact-match or agreed business validation). For high-stakes workflows we tune to an agreed production target together.
Upload a document and hit Extract to JSON — structured data appears here in the exact shape your systems need.
A representative extraction — in an engagement we shape it to your exact fields, formats and downstream systems.
Across a 100-document pilot we extracted report number, country, assessment type, compliance result and evidence text from multilingual PDFs. Domain validation rules resolved ambiguous assessment language before data entered the customer's workflow — reaching 97.2% exact-match across six critical fields after tuning.
Representative of a real engagement; we confirm your numbers in a pilot on your own documents.
Accuracy is a business decision, not a spec
How accurate you need to be depends on what an error costs. We'll get you to the right tier — no further, no less.
Good enough to act on
Out of the box on clean documents. Ideal for triage, internal search, first-pass sorting and low-stakes automation where a human still glances at the result.
- Pick doc type + domain, get structured JSON
- Live in days, minimal setup
When a mistake costs money
For payments, compliance, KYC, claims and health data — where a wrong field means a wrong payout, a breach or a rejected filing. The last 10–20% is real work, and it's what we do.
- Domain validation rules & cross-checks
- Human-in-the-loop review of low-confidence fields
- Integration into your systems + drift monitoring
Documents that still consume valuable manual effort
Finance & accounting
Invoices, POs, receipts, bank statements, tax forms.
Identity & KYC
Passports, IDs, licenses, proof of address.
Healthcare
Prescriptions, lab reports, claim & auth forms.
Insurance
Claims, ACORD forms, policies, estimates.
Legal & contracts
Contracts, deeds, titles, court filings.
Logistics & trade
Bills of lading, waybills, customs, POD.
Lending & mortgage
Loan packets, pay stubs, appraisals, titles.
Food & product labels
Nutrition panels, ingredients, specs.
Handwriting, tables & more
Forms, engineering drawings, archives. If your team reads it manually today, we'll assess whether it can be reliably structured.
From a schema to production accuracy
Define the schema
Pick doc type & domain, agree the fields and formats you need out.
Pilot on your docs
Run your real documents, measure accuracy per field, see the confidence.
Tune & integrate
Validation rules, review queue, and a pipe into your ERP/CRM/DB.
Support & hold accuracy
Accuracy SLAs and format-drift monitoring as your documents change.
Consultants who ship production AI
Off-the-shelf OCR APIs stop at raw text. We own the last mile — schema design, validation, human review, integration and the accuracy you can actually depend on.
Questions, answered
How is this different from a generic OCR API?+
Generic APIs give you raw text or loose fields. We deliver structured data mapped to your schema, validated against domain rules, with low-confidence fields routed to human review and the output piped into your systems. That's the difference between 85% and >95%.
How is accuracy measured?+
At field level, using exact-match or an agreed business-validation rule per field — not a vague document-level average. Typical self-serve accuracy is 80–90% overall on clean, consistent documents, and individual machine-printed fields may exceed 90%. During the pilot we set and measure the target separately for each critical field.
What happens to our documents? Are they retained?+
Your documents are processed only to produce your output and are not used to train shared or third-party models. Retention is set by you — including no-retention and in-your-environment options. No document content is sent to public consumer AI services.
Which documents can you handle?+
Invoices, IDs, medical and insurance forms, contracts, logistics and lending packets, product labels, plus handwriting, tables and engineering drawings. If it's on a page, we can structure it.
Where does processing run, and which models?+
On private, enterprise AI models — no public consumer AI services. Deploy as SaaS in Echno Technologies' cloud, or in your own VPC / on-premises for qualifying enterprise workloads (typically higher volume). Below the confidence threshold, the field is flagged and routed to human review before it enters your workflow.
How is it priced?+
Pricing depends on document complexity, number of fields, monthly volume, review requirements and deployment model. Pilots are scoped separately from production processing; production is typically per-document or per-field, or infrastructure-plus-consulting for private deployment. We'll scope it transparently on the call.
Book a consultation.
Tell us the document type and the accuracy you need. We'll scope a pilot on your own documents and show you the structured output — and the confidence behind every field.
- A schema for your document type
- A pilot on your own documents
- A path to >95% · your cloud or ours
Book a consultation
Pick a slot — we'll send the calendar invite.
