Intelligent Document Processing Services

Automated extraction of vendor name, invoice number, invoice date, line items (description, quantity, unit price, line total), subtotal, tax amount and tax code, total amount due, payment terms (Net 30, Net 60), bank details (IBAN, sort code, account number), and purchase order reference from supplier invoices in any format -- digital PDF, scanned paper, photographed receipt, EDI 810, or e-invoice XML (EN 16931 / PEPPOL BIS Billing 3.0). OCR engine selection based on document quality: Azure Document Intelligence (formerly Form Recognizer) Invoice model for consistent high-quality PDFs; AWS Textract AnalyzeExpense API for mixed-quality scanned invoices; custom fine-tuned LayoutLMv3 for proprietary or unusual invoice formats. Validation against ERP master data: extracted vendor name normalised and matched against vendor master using Levenshtein distance similarity (configurable threshold, typically 0.85+); extracted PO reference cross-checked against open POs (amounts within ±2% tolerance for goods, exact match required for services); extracted line items matched to PO line items with quantity and price tolerance checks; DUNS number or VAT registration number validated against the vendor master as a secondary identity check. Two-way and three-way matching: two-way (invoice vs PO) for service invoices; three-way (invoice vs PO vs goods receipt) for product invoices confirming physical receipt before payment approval is triggered. Approval routing: invoices below £500 auto-approved with coding applied; £500--£5,000 routed to cost centre manager; above £5,000 routed to department director; above £25,000 requires finance director sign-off. Integration with SAP (IDOC, OData), Oracle ERP Cloud (REST), NetSuite (SuiteTalk), Dynamics 365 BC (OData v4), QuickBooks Online (API), and Xero (API) for automatic AP posting on approval.

Extraction of key contract terms from supplier agreements, customer contracts, NDAs, and service agreements in PDF or Word format -- surfacing the data that typically requires a paralegal or junior lawyer to manually review and log into a contract management system. Fields extracted: contracting parties (legal entity names and registered addresses), effective date, expiry date, notice period, auto-renewal clause (including the number of days' notice required to prevent auto-renewal), payment terms, liability cap (absolute amount or formula such as 12 months of fees), indemnification obligations, IP ownership clauses, governing law, and dispute resolution mechanism. Extraction technology: GPT-4o or Claude 3 Opus with structured output (JSON schema enforcement via function calling or tool use) for semi-structured clause extraction, guided by a contract-specific system prompt that defines the target fields and the extraction instructions per field type; Azure Document Intelligence for the initial layout parsing and section detection that provides the context boundaries passed to the LLM. Confidence scoring per clause: fields where the model is uncertain (ambiguous drafting, clause not present in the contract, or conflicting provisions in multiple sections) are flagged with a low confidence score for legal review rather than silently extracted with an incorrect value. CLM integration: structured contract data delivered to Ironclad, ContractSafe, Juro, Conga, or custom contract databases via REST API; Salesforce CRM linked opportunities updated with contract effective date and renewal date; Slack or email alert 90, 60, and 30 days before renewal or expiry dates. Risk flag detection: LLM-identified clauses deviating from standard templates (uncapped liability, unlimited termination rights, non-standard IP assignment) flagged separately for legal team review before signature.

Document classification and data extraction for high-volume intake workflows where a single submission comprises multiple document types that must be processed together before a routing or eligibility decision is made. Insurance claims: claim form classification and key data extraction (claimant identity, policy number, incident date, claimed amount, incident description); supporting document classification (medical certificates, police reports, photographs, repair estimates) with content relevance scoring for the claim type; cross-document consistency validation (claim date consistent with supporting medical record dates, claimed item matches policy schedule); automated completeness check triggering a request-for-information (RFI) email when required supporting documents are absent before the claim enters the adjudication queue. Loan and credit applications: application form extraction (applicant identity, employment status, income declaration, loan amount requested, loan purpose); document classification for supporting evidence (bank statements, payslips, P60, proof of address); income validation comparing declared income against bank statement deposits; automated credit bureau lookup triggered on application receipt with the extracted applicant identity fields (Experian/Equifax/TransUnion API integration); eligibility scoring rules applied before human underwriter review. Government and grant forms: field extraction from standardised government forms (HMRC, DWP, local authority forms) with lookup against reference data tables (HS codes, SIC codes, local authority reference numbers) for field validation. Multi-document correlation: documents from the same submission linked by submission ID and presented as a unified record in the review interface so reviewers see all supporting documents alongside the primary form rather than processing each document independently.

OCR extraction from retail receipts, fuel receipts, toll receipts, restaurant receipts, and mixed-format expense documents submitted as JPEG, PNG, or PDF from mobile device cameras, scanners, or email attachments. Image pre-processing pipeline: OpenCV-based deskew and perspective correction to normalise rotated or angled photographs; contrast enhancement and noise reduction to improve OCR accuracy on faded thermal receipts; resolution normalisation before OCR engine processing. OCR engine: Google Cloud Vision API or AWS Textract for field-level extraction from standard receipt layouts; custom fine-tuned PaddleOCR or EasyOCR models for proprietary receipt formats (fuel retailers, toll operators, industry-specific vendors) where the generic cloud OCR performance falls below threshold. Fields extracted: merchant name, merchant address, merchant VAT/tax registration number, transaction date and time, payment method (card/cash), line items (description and amount), subtotal, tax amount and rate, total amount. Fuel receipt specialisation: fuel volume (litres/gallons), fuel type (unleaded, diesel, electric), unit price per litre/gallon, and odometer reading extracted where printed on the receipt -- feeding mileage and fuel cost tracking without separate manual entry. Expense policy validation: extracted merchant category (MCC code from merchant name lookup or Google Maps Places API category) checked against policy rules (no alcohol purchases, meals above £50 per person require approval, overnight accommodation requires prior authorisation); policy violation flagged in the review queue with the specific policy rule cited. Integration: Concur, Expensify, Certify, SAP Concur, and custom finance platforms via REST API or file export. Our gas station OCR system processes 20,000+ transactions per day -- a proven reference for high-volume, mixed-quality receipt processing at production scale.

Structured data extraction from medical records, discharge summaries, lab reports, referral letters, prior authorisation forms, and clinical assessment forms -- reducing the manual data abstraction work that clinical coders, case managers, and prior auth coordinators perform. Entity extraction using clinical NLP: scispaCy with the en_core_sci_lg model for named entity recognition of medical concepts (diagnoses, medications, procedures, anatomy); UMLS and SNOMED CT concept normalisation mapping extracted clinical terms to standardised terminologies for downstream coding and analytics; medication extraction capturing drug name (brand and generic), dose, frequency, route of administration, and prescribing physician. ICD-10 code suggestion: extracted diagnoses mapped to candidate ICD-10 codes using UMLS CUI mapping and a LLM-assisted code selection step that presents the top 3 candidate codes with the supporting clinical evidence for the clinical coder to review and confirm. Prior authorisation processing: clinical information extracted from referral letters and clinical notes, mapped to the payer's prior auth criteria fields, and submitted to the payer's prior auth platform (Availity, NaviMedix, or payer-specific APIs) with the supporting clinical evidence attached. HIPAA compliance architecture: documents processed within your cloud VPC (no data transmitted to third-party LLM providers without a BAA in place; Azure OpenAI or AWS Bedrock used for private LLM inference where required); PHI access logged at the field level with user identity and timestamp; data retention and deletion policies enforced per HIPAA Safe Harbor de-identification rules. EHR integration: extracted structured data delivered to Epic (FHIR R4 API), Cerner (FHIR R4), Athenahealth (API), and custom EHR systems via REST or HL7 v2 message.

Automated processing of the document set required for international trade shipments -- bills of lading, commercial invoices, packing lists, certificates of origin, phytosanitary certificates, dangerous goods declarations, and import/export customs entries. Document classification: incoming shipment documents classified by type using a fine-tuned classifier (DistilBERT or a vision model for scanned documents with layout features) so each document type routes to the appropriate extraction model rather than a generic extraction approach that underperforms on the structural differences between a bill of lading and a commercial invoice. Commercial invoice extraction: shipper and consignee details, country of origin, HS code per line item, quantity, unit of measure, unit value, total value, currency, and Incoterms. Bill of lading extraction: carrier, vessel name and voyage number, port of loading, port of discharge, container number, seal number, gross weight, and freight payment terms. HS code validation: extracted HS codes validated against the latest WCO HS tariff schedule (8-digit codes validated for the importing country's tariff schedule -- UK Global Tariff, EU Combined Nomenclature, US HTS); codes that exist in the schedule but are incorrect for the described goods flagged using a product description-to-HS code consistency check (LLM-based, surfacing potential misclassification for customs broker review). Customs entry pre-population: validated document data pre-populates CBP Form 3461 (Entry/Immediate Delivery), CBP Form 7501 (Entry Summary), or the equivalent UK CDS (Customs Declaration Service) SAD form in your customs filing platform (Descartes, DAKOSY, CDS API, or in-house TMS). Integration with SAP Transportation Management, Oracle TMS, MercuryGate TMS, and custom logistics platforms via REST API or EDI.