AI‑powered document intelligence.
An educational prototype developed at Frankfurt School - AI for Finance Certificate Course, exploring how Artificial Intelligence can transform financial document processing.
This is a non-commercial learning project. No real customer data is used.
AuroraBank DocReader 3000
AI-Powered Document Intelligence
Reinventing document trust. Exploring how artificial intelligence can make financial data processing faster, more transparent, and verifiable.
The Architecture of Learning
OCR, natural-language extraction, and semantic search merge into a transparent cycle of continuous learning and improvement through human feedback.
Technical Foundation
Modular architecture with PHP backend, Python AI worker, and Docker infrastructure. MySQL, Qdrant, and Redis ensure reliability and real-time responsiveness.
Research by Design
A proof of concept for intelligent, auditable automation. Inviting innovators to explore how trust, compliance, and AI evolve together.
System Overview
AuroraBank demonstrates a modular AI pipeline: from document ingestion to structured, explainable outputs. Each step is traceable and can be analyzed for performance and accuracy.
The Problem
Manual Document Processing: Banks spend countless hours manually processing invoices, contracts, and compliance documents. This is slow, error-prone, and expensive - exactly what AI should solve.
The Solution
AI-Powered Automation: DocReader 3000 automatically extracts text, validates data, and makes documents searchable. Users can ask questions in natural language: "Show me all invoices from Hamburg" or "Calculate total expenses."
Banking Use Case
Real-World Application: Process loan applications, vendor invoices, and regulatory filings. Reduce processing time from hours to seconds while maintaining accuracy and compliance.
AI, on your terms
Clear boundaries
AI that stays in scope, built for predictable outcomes.
Human oversight
Review flows that keep people in control.
Learning system
Improves with use — templates and patterns, not guesswork.
Trustable outputs
Every result is explainable and ready to share.
Privacy first
Minimal data, masked where needed, switchable integrations.
Fast to value
From upload to insight with a clean, modern UI.
Explainable AI
Every document processed by AuroraBank passes through transparent steps — OCR, NLP, classification, and structured storage. The system highlights how AI decisions can be made visible and verifiable in a financial context.
Transparent Processing
Each document follows a clear path: OCR extraction → NLP analysis → field classification → structured storage. Every step is logged and auditable.
Confidence Scoring
AI decisions include confidence levels for each extracted field. Low-confidence results are flagged for human review, ensuring accuracy in financial contexts.
Decision Traceability
Track exactly why the AI made specific classifications or extractions. View the source text, applied patterns, and reasoning behind each automated decision.
What you get
Modern Review UI
Designed for speed and accuracy.
Template learning
Consistent results on recurring layouts.
Deterministic answers
Guardrails for reliable interactions.
Semantic discovery
Find the right parts across pages.
Built‑in privacy
Respectful by default; configurable when needed.
Easy export
Data you can act on — without friction.
AI Pipeline Production Ready
Advanced document intelligence powered by modern AI/ML technologies
Document Processing Pipeline
Purpose: Transform semi-structured financial documents into fully structured, validated, and actionable business data through an iterative AI-powered pipeline with human oversight, continuous learning feedback loops, and multi-stage validation gates.
Continuous improvement through feedback loops
Multi-stage quality assurance checkpoints
Graceful handling of validation failures
Document Ingestion & Validation
Multi-Format Ingestion
PDF, JPG, PNG, TIFF support
Security & Compliance
Authentication & authorization
AI-Powered Text Extraction & Analysis
Advanced OCR Engine
PaddleOCR + Tesseract hybrid
Field Extraction AI
EU EN16931 compliant extraction
Human-in-the-Loop Quality Assurance
Expert Review Interface
Domain expert validation & correction
Adaptive Learning Engine
Real-time pattern generation & model updates
Iterative Re-processing (Conditional Loop)
Enhanced Re-extraction
Apply learned patterns to improve accuracy
Quality Gate Decision
Automated quality assessment & routing
Complete Data Storage & Indexing
Structured Data Storage
MySQL/PostgreSQL with ACID transaction safety
Document File Storage
Secure file system for original documents
AI Intelligence & Search
Vector Database (Qdrant)
Semantic search infrastructure for AI operations
Hybrid RAG Assistant
Intelligent document analysis with dual-mode processing
Multi-Modal Intelligence
Advanced reasoning & citation system
Multi-Stage Validation Gateway
Contract Compliance Validator
Validates stored contract data against legal rules
Sanctions Screening Engine
Screens stored entity data against watchlists
Financial Data Validator
Validates stored financial data for compliance
AI Fraud Detection
Analyzes stored transaction patterns for fraud
Business Integration & APIs
Business Intelligence
Actionable insights & recommendations
Payment & ERP APIs
Seamless integration with business systems
External System Integration
Secure connectivity to enterprise systems
Why This Pipeline Excels
High Performance
Highest accuracy with sub-second response times
Scalable Architecture
Docker-based microservices with horizontal scaling capability
Self-Improving AI
Continuous learning from user feedback with pattern recognition
Technology Stack
AI & Machine Learning
Data & Storage
Backend & Infrastructure
Frontend & UX
Security & Compliance
File Processing
Open Source & Frontier AI Models
This educational project demonstrates the combination of Open Source Software with modern Frontier AI Models for transparent and cost-effective solutions.
Open Source Foundation
Cost-effective, transparent and adaptable technologies form the foundation of the system.
Frontier AI Models
State-of-the-art AI models via APIs for intelligent document analysis and natural language interaction.
Hybrid Architecture
Intelligent combination of local processing and cloud-based AI services for optimal performance.
Live Interactive Demo
Experience the AI-powered document processing system in action
DocReader 3000
Upload documents, search semantically, and access the review interface
Sign in to DocReader 3000
Enter your credentials to access the document processing portal
AI Document Assistant
Ask natural language questions about your documents and get intelligent, cited answers powered by GPT-4o and semantic search.
Health monitor
Real-time infrastructure monitoring
Document Processing
AI-powered document analysis
Vector Search
OpenAI-powered semantic search
Performance
System responsiveness
Processing Queue
Document workflow status
OCR Accuracy
Text recognition quality
Storage Usage
Capacity management
DocReader 3000 Hybrid RAG Monitor
Real-time AI system transparency for educational insights
Concept Demonstrations
Future vision & architectural concepts
System Orchestrator
The control layer connecting contracts, invoices, and compliance checks
Contract Validator
Automated contract compliance verification
Sanctions Validator
Real-time sanctions list screening
Invoice Processing API
AI-powered invoice extraction & validation
AI Fraud Detection
Real-time document analysis and anomaly detection for banking security
Active Detection Algorithms
Recent Fraud Alerts
Overall Risk Assessment
Security & Privacy
Educational prototype with enterprise-grade security concepts for learning purposes
Authentication & Authorization
Demonstrates Basic Auth implementation with proper credential validation and session management for educational purposes.
Data Protection
Shows how sensitive document data can be protected with encryption, access controls, and privacy-by-design principles.
Audit & Compliance
Demonstrates comprehensive logging and audit trails essential for financial document processing systems.