Document Intelligence & OCR
Turn paper and digital documents into structured, actionable data. Invoice processing, contract analysis, company forms extraction with multi-stage pipelines that validate, route, and sync to your enterprise systems automatically.
Multi-Stage OCR Pipeline
Documents move through capture, classification, OCR, field extraction, validation, and routing. Each stage is configurable per document type, with confidence scoring and exception flagging at every step.
Intelligent Document Classification
Automatically identifies whether an incoming document is an invoice, purchase order, contract, ID card, or custom type — using layout-aware models that understand document structure, not just text.
Custom Validation Rules
Business rules run after extraction: cross-reference invoice totals, validate VAT numbers, check supplier codes against your master data. Documents that fail validation are flagged for human review.
ERP Sync & Automated Routing
Extracted and validated data flows directly to your ERP (SAP, Oracle, Microsoft Dynamics), DMS, or custom systems via API. Approved documents are archived, rejected ones trigger workflow tasks.
The Cost of Manual Document Processing
Enterprise document workflows like invoices, contracts, HR forms, compliance filings consume an enormous amount of human time. A typical accounts payable team manually processes invoices by opening each document, identifying the vendor, reading line items, cross-referencing against purchase orders, entering data into the ERP system, and routing for approval. Each invoice takes 5 to 15 minutes of manual handling. At scale of thousands of invoices per month this becomes a major operational cost and a source of data entry errors that cascade through financial reporting.
AI-powered document intelligence automates the entire pipeline: documents are ingested, classified, OCR-processed, field-extracted, validated against business rules, and routed to downstream systems — with human review only for exceptions that fall below confidence thresholds. Processing time drops from minutes per document to seconds, accuracy improves because validation rules are applied consistently, and your team focuses on exceptions rather than routine data entry.
Document Types We Handle
Pipeline Architecture
Each document processing pipeline is built as a sequence of modular stages, configurable per document type:
Ingestion and preprocessing
Documents arrive via email, file upload, API, or watched folder. Scanned documents are deskewed, denoised, and enhanced for optimal OCR quality. Multi-page documents are split or merged as needed.
Classification
A layout-aware classifier (LayoutLM or Donut) identifies the document type based on visual structure and content — not just keywords. This determines which extraction template and validation rules to apply.
OCR and field extraction
PaddleOCR or Tesseract extracts raw text. A fine-tuned extraction model then maps the text to structured fields: vendor name, invoice number, line items, totals, dates. Confidence scores are assigned to each extracted field.
Validation and enrichment
Business rules validate extracted data: does the vendor exist in your master data? Do line item totals sum to the invoice total? Is the VAT number valid? Fields below confidence thresholds or that fail validation are flagged for human review.
Routing and integration
Validated documents are pushed to your ERP, DMS, or accounting system via API. Approval workflows are triggered based on document type and value thresholds. Rejected documents enter an exception queue with clear reasons for rejection.
Why On-Premise for Document Processing
Documents processed by OCR pipelines often contain highly sensitive information: financial data, personal employee information, patient records, contractual terms, and proprietary business details. Sending these documents to a cloud OCR service means transmitting that data outside your network. For organisations subject to HIPAA, GDPR, or internal data governance policies, this creates compliance exposure. Our on-premise document intelligence pipelines process everything locally — no document image, no extracted text, and no structured output ever leaves your infrastructure. This also eliminates per-page cloud OCR costs, which can become significant at enterprise document volumes.
Technology Stack
OCR models and processing infrastructure