What is Document AI and how is it different from standard OCR?

Standard OCR converts an image of text into machine-readable text. Document AI goes further: it extracts specific fields and values (not just raw text), classifies the document by type and routes it to the correct workflow, validates extracted data against expected formats and cross-referenced values, and flags inconsistencies for human review. Almanor AI's Document AI is also trained specifically on your document types — understanding the structure, terminology, and field locations of the documents your organisation actually receives, not generic templates.

What document formats does Document AI handle?

Almanor AI's Document AI handles PDFs (both text-based and scanned image), image files (JPEG, PNG, TIFF), email attachments, Microsoft Office documents (Word, Excel), and structured data formats (JSON, XML, CSV). For scanned documents, the processing pipeline includes image pre-processing to handle rotation, skew, and degraded scan quality before extraction. Multi-page documents and document packages (multiple documents submitted together) are handled with automatic separation and classification.

How accurate is document extraction in practice?

Almanor AI achieves 98%+ extraction accuracy in production across standard regulated industry document types — P60s, bank statements, insurance claims, government forms, KYC documents, and clinical records. For documents below the confidence threshold, the system flags the specific fields requiring human review rather than passing uncertain extractions downstream. The practical effect is that humans review exceptions rather than entire documents, dramatically reducing the manual effort while maintaining accuracy where it matters.

How does Document AI handle documents in multiple languages?

Document AI supports 30+ languages with domain-specific training for each. This is not a translation layer — the models are trained specifically on documents in each language, understanding the terminology, format conventions, and regulatory vocabulary of each market. A Dutch insurance claim form is processed by a model trained on Dutch insurance documents, not an English model with the text translated first. This produces materially higher accuracy for non-English documents than generic multilingual OCR solutions.

What happens with documents that the AI cannot process confidently?

Documents below the confidence threshold are flagged for human review with a structured package: the document image, the extracted fields the AI is confident about, and the specific fields where confidence is low. The human reviewer validates or corrects the flagged fields — and this correction is captured as a training example for the next retraining cycle. Over time, the proportion of documents requiring human review decreases as the model learns from corrections.

Document AI for Regulated Industries | Extract, Classify & Validate

THE CAPABILITY

Extract, classify, and validate. Any document. Any format. At scale.

From W-2s and K-1s to planning applications and clinical referrals — Almanor AI's Document AI processes any document type with extraction models fine-tuned on domain-specific document libraries.

Extracted data is cross-validated against source documents and business rules before being passed downstream — eliminating the manual review step that creates backlogs in every regulated operation.

Ingestion

Documents are ingested from any source — email, upload portal, scanning station, or API — in any format including scanned images and handwritten forms.

Classification

Each document is classified by type, entity, and processing priority — routing it to the correct extraction pipeline automatically.

Extraction

Structured data is extracted from each document with confidence scores — flagging low-confidence fields for human review rather than passing them silently downstream.

Validation & downstream routing

Extracted data is validated against business rules and cross-referenced against existing records — then routed to the appropriate downstream system with a full audit trail.

PERFORMANCE

What Document AI delivers in practice

98%+ extraction accuracy

Extraction models fine-tuned on domain-specific document libraries consistently outperform generic OCR and extraction tools on regulated-sector documents.

Any format, any language

Native support for PDFs, scanned images, Word documents, and emails — in 30+ languages — with no pre-formatting required.

Full audit trail

Every extraction decision is logged with source document reference, confidence score, and validation outcome — satisfying audit and regulatory requirements in every sector we serve.

THE DOCUMENT PROBLEM IN REGULATED INDUSTRIES

Regulated industries generate billions of documents per year. Most of them are still processed manually. The cost, latency, and error rate of manual document handling is the single largest operational inefficiency in regulated sectors.

A financial services firm processes thousands of documents per day — account applications, KYC packs, insurance claims, regulatory filings, customer correspondence. A government agency receives permit applications, FOI requests, benefits claims, and planning documents. A healthcare provider handles referral letters, prior authorisation requests, clinical records, and insurance documents. In every case, the document handling is labour-intensive, error-prone, and a bottleneck on everything downstream.

Almanor AI's Document AI is trained specifically for regulated industry document types — not generic OCR, not a general-purpose AI prompted to extract text. The difference is significant: a system trained on your specific document library understands the structure of a Companies House filing, knows where the net profit figure appears on your P&L format, and can distinguish a standard claims form from one with inconsistencies that require manual review.

The result is 98%+ extraction accuracy, full classification with routing logic, and a complete audit trail for every document processed — at any volume, any format, and any language.

98%+

extraction accuracy across P60s, bank statements, insurance claims, government forms, legal documents, and clinical records — validated in production environments.

30+

languages supported with domain-specific training for each — not generic translation, but language-specific models calibrated to the regulatory terminology of each market.

85%

reduction in document handling time across accounting firm deployments — from document receipt to structured output ready for professional review.

DOCUMENT TYPES WE PROCESS

Trained on the documents that actually matter in regulated environments.

Financial Documents

Bank statements, P60s, P11Ds, P45s, interest certificates, dividend statements, company accounts, management accounts, tax calculations, payslips.

Government & Legal Documents

Permit applications, FOI requests, benefits claim forms, planning documents, statutory returns, Companies House filings, legal notices, court documents.

Insurance & Claims

Insurance application forms, claims submissions, medical reports, assessor reports, policy documents, endorsements, and supporting evidence packages.

KYC & Compliance Documents

Passports, driving licences, utility bills, bank letters, corporate structure documents, beneficial ownership forms, sanctions screening outputs.

Clinical & Healthcare Documents

Referral letters, discharge summaries, clinical notes, prior authorisation requests, prescription records, and medical certificates.

Customer Correspondence

Emails, letters, complaint forms, and enquiry correspondence — classified by intent, routed to the correct team, and summarised with extracted key information.

FREQUENTLY ASKED QUESTIONS

Every regulated industry runs on documents. We automate them.

Extract, classify, and validate. Any document. Any format. At scale.

What Document AI delivers in practice

98%+ extraction accuracy

Any format, any language

Full audit trail

Regulated industries generate billions of documents per year. Most of them are still processed manually. The cost, latency, and error rate of manual document handling is the single largest operational inefficiency in regulated sectors.

Trained on the documents that actually matter in regulated environments.

Common questions about this service.

Stop processing documents manually.

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