Capital Markets FinTech Achieves 99% Document Accuracy and Real-Time Deal Intelligence with Agentic AI

Financial Services

Capital Markets FinTech Achieves 99% Document Accuracy and Real-Time Deal Intelligence with Agentic AI

Client

Capital Markets FinTech

Back to Case Studies

Overview

Our client is a leading capital markets fintech company known for its innovative approach to deal intelligence and document management. The company serves major investment banks and financial institutions across Asia Pacific, processing thousands of financial documents daily.

This project involved the deployment of a highly intelligent, AI-powered document processing pipeline leveraging AWS Bedrock and custom agentic AI workflows. Pixel ML was tasked with improving document accuracy, automating deal intelligence extraction, and reducing manual processing overhead.

Challenges

  • Document Accuracy: The client's existing OCR and extraction pipeline achieved only 82% accuracy on complex financial documents, requiring extensive manual review.
  • Speed of Processing: Processing a single deal document took an average of 45 minutes, creating bottlenecks during high-volume periods.
  • Scalability: The legacy system couldn't handle peak loads during quarterly earnings seasons, leading to delays and missed deadlines.
  • Data Integration: Financial data needed to be extracted and normalized across 15+ different document formats from various counterparties.

Solution

Agentic AI Pipeline

We designed and implemented a multi-agent AI system that orchestrates document processing through specialized agents:

  1. Document Classification Agent — Automatically identifies document types (term sheets, prospectuses, financial statements) with 99.2% accuracy.
  2. Data Extraction Agent — Extracts key financial metrics, terms, and conditions using fine-tuned LLMs on AWS Bedrock.
  3. Validation Agent — Cross-references extracted data against market data and historical records to flag anomalies.
  4. Integration Agent — Normalizes and routes processed data to downstream systems.

Cloud Architecture

Built on AWS with infrastructure-as-code:

  • AWS Bedrock for foundation model access (Claude, Titan)
  • Amazon S3 for document storage with intelligent tiering
  • AWS Lambda for serverless processing pipelines
  • Amazon DynamoDB for real-time metadata management
  • Amazon CloudWatch for monitoring and alerting

Results

The implementation delivered transformative results within the first 3 months:

  • 99% document accuracy — up from 82%, virtually eliminating manual review
  • 3-minute processing time — down from 45 minutes per document (93% reduction)
  • 10x throughput capacity — seamlessly handling peak quarterly volumes
  • $2.4M annual savings — from reduced manual processing and faster deal execution
  • Zero downtime — during the transition from legacy to new system

"Pixel ML's agentic AI solution has fundamentally transformed how we process deal documents. What used to take our team hours now happens in minutes with higher accuracy than we ever achieved manually."

— VP of Technology, Capital Markets FinTech

Technology Stack

| Category | Technologies | | --- | --- | | AI/ML | AWS Bedrock, Claude, Custom Fine-tuned Models | | Cloud | AWS Lambda, S3, DynamoDB, CloudWatch | | Processing | Python, LangChain, Custom Agents | | Integration | REST APIs, Event-driven Architecture | | Monitoring | CloudWatch, Custom Dashboards |