Multilanguage Document Extraction Agent
Standardize multilingual documents, enabling accurate and compliant policy handling
Description
Challenge:
Insurers operating across regions receive claim forms, medical records, invoices, and affidavits in multiple languages. Manual translation and validation is slow, error-prone, and can lead to inconsistent adjudication, delays, and compliance risks. Without automation, multilingual submissions require extra resources and increase turnaround time, impacting customer satisfaction and operational efficiency.
How It Works:
The Multilanguage Document Extraction Agent combines OCR, NLP, and translation models to extract key entities such as names, policy numbers, diagnosis codes, treatment details, and financial values from documents in any supported language. Extracted entities are translated into a base language, normalized (dates, currency, ICD codes), and validated against internal systems (PAS, CRM, Claims). Low-confidence or ambiguous terms are flagged for manual review. Structured, language-normalized JSON outputs enable consistent processing and integration with claims, underwriting, and policy workflows while maintaining a full audit trail.
Benefits:
Achieves 90–95% accuracy in multilingual entity extraction and translation
Reduces dependency on human translators by 65–75%
Speeds up multilingual claim processing by ~50%
Ensures 100% normalization of dates, currencies, and medical codes
Maintains 95%+ consistency with internal validation records
Enables seamless cross-border claims adjudication and regulatory compliance
Features
This agent ensures accurate extraction, translation, and normalization of multilingual documents, allowing insurers to process claims consistently and compliantly across geographies.
Features & Capabilities:
Document Ingestion: Accepts PDFs, images, and scanned forms in multiple languages
Language Detection: Automatically identifies source language using ML classifiers
OCR + NLP: Extracts raw text and entities with language-specific recognition models
Translation & Normalization: Converts text into base language, standardizes dates, currencies, and ICD codes
Entity Recognition: Identifies policy numbers, claimant names, diagnoses, and financial values
Validation: Cross-checks translated data against PAS, CRM, and Claims records
Confidence Scoring: Assigns scores to extracted and translated entities
Exception Handling: Flags low-confidence or untranslatable text for manual review
Integration: Outputs structured, language-normalized JSON or XML for downstream workflows
Operating Blueprint
Knowledge Sources:
Multilingual claim forms, invoices, affidavits, and medical records
CRM/Member Database – claimant identities across languages
PAS – coverage details, policy identifiers, exclusions
Claims History Database – past claims across regions
Multilingual dictionaries – medical, financial, and legal terms
Currency repository – conversion and formatting rules
Business Rules:
Language Detection: Flag unidentified languages for manual processing
Translation Accuracy: Require ≥90% confidence before auto-accept
Policy Identifier Normalization: Standardize identifiers across language variants
Currency Conversion: Normalize foreign amounts with real-time or configured rates
Date Standardization: Convert to ISO format (YYYY-MM-DD)
Medical Term Mapping: Map multilingual terms to ICD-10 codes
Documentation Completeness: Ensure mandatory fields are extracted and translated
Confidence Threshold Enforcement: Route items <85% accuracy for human validation
Tool Workflow:
Upload document in any supported language
Detect source language automatically
Extract text and entities via OCR + language-specific NLP
Translate and normalize extracted data
Cross-check against PAS, CRM, and Claims records
Assign confidence scores and route low-confidence items for review
Output structured JSON/XML for integration
Maintain audit logs for compliance and traceability
Badges
Classification
Capabilities
