Hypodossier: Fintech Automation
Automating enterprise mortgage document administration through intelligent extraction and classification pipelines. We built an AI-driven platform capable of recognizing over 250 document types and extracting 500+ granular data fields to eliminate manual bottlenecks for enterprise lenders.
95% Accuracy
Recognition
500+ Data Fields
Extraction
250+ Document Types
Classification
Challenge & Scope
Requirements
Eliminating manual data entry for irregular financial documents
Achieving high-accuracy (95%+) recognition for 250+ distinct document types
Strict data privacy and GDPR regulatory adherence
Scaling the extraction pipeline to handle massive document batches
Strategic Objectives
Automate complex mortgage document processing with high precision and GDPR compliance.
Key Deliverables
Technical Execution
Intelligent Pipeline
Developed a sophisticated vision pipeline that automatically cleans, cuts, and rotates documents, ensuring they are perfectly formatted for AI classification.
250-Type Classifier
Engineered an AI classification engine that identifies and names over 250 specific mortgage and financial document types with 95% accuracy.
500-Field Extraction
Implemented a deep extraction engine that captures over 500 data points (income, debt, asset values), enabling total automation of lender workflows.
Technical Stack
Languages/AI
Python
Computer Vision Pipelines
NLP
Web Stack
Django Ninja
React
TypeScript
Database
PostgreSQL
Compliance
GDPR / Global Privacy Standards
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Features & Outcomes
95% Recognition
Drastic reduction in manual verification overhead.
Auto-Cleanup
Optimized document legibility and storage size.
Lending Dashboard
Single source of truth for all processed mortgage files.
Client Benefits
Massive operational cost savings compared to manual high-cost labor
Instant scalability to handle seasonal mortgage application spikes
Access to specialized AI and vision engineering talent in Ethiopia
Seamless collaboration across European time zones (UTC+3)
Strategic Outcomes
Eliminated time-consuming manual document administration for lenders
Allowed financial specialists to focus on high-value customer relationships
Established a record-breaking accuracy rate for complex document recognition
Ensured full technical compliance with standardized data residency and GDPR laws
System Interfaces
Project Team
Sami
Full-stack Developer
Vision Pipelines & Backend Engineering