ScoreSweep

Turn painful credit and consumer report audit into minutes. ScoreSweep uses AI to explains and flags errors, drafts dispute letters or generates call scripts and lets you take control of your data.

Comment

ScoreSweep: AI-Powered Credit Report Analysis & Dispute Automation

🌟 Inspiration

After a move to a new state, three insurers denied my auto-coverage applications.
My driving record was clean, my credit decent, and no one could tell me why.
Months later I discovered they were pulling a 112-page LexisNexis C.L.U.E. report
crammed with claim numbers, addresses, and even vehicles that weren’t mine.
It took two full days, a spreadsheet, and a migraine to decode the report and learn how
to dispute each error.

Credit reports are the foundation of financial freedom, yet millions of Americans struggle with inaccurate information that unfairly impacts their credit scores. The inspiration for ScoreSweep came from a simple yet powerful realization: what if AI could democratize access to professional-grade credit repair services?

Traditional credit repair companies charge hundreds of dollars and take months to dispute errors. Meanwhile, consumers who try to dispute errors themselves often struggle with:

  • Understanding complex credit report language
  • Identifying subtle but impactful errors
  • Writing effective dispute letters that get results
  • Navigating the bureaucratic maze of credit bureaus

We envisioned a world where anyone could upload their credit report and instantly receive:

  • AI-powered analysis that catches errors human eyes might miss
  • Professional dispute letters generated in seconds, not weeks
  • Actionable insights with confidence scores and priority rankings
  • Complete automation from analysis to dispute generation

🚀 What ScoreSweep Does

ScoreSweep is a comprehensive AI-powered platform that transforms credit repair from a complex, expensive process into a simple, accessible experience:

Core Features:

  • Intelligent Document Analysis
  • AI-Powered Error Detection
  • Comprehensive Issue Dashboard
  • Professional Document Generation
  • Smart Workflow Management

🛠 How We Built It

Architecture Overview

ScoreSweep is built on a modern, scalable architecture designed for performance, security, and user experience:

Frontend (React/TypeScript) ↔ Backend (FastAPI/Python) ↔ AI Services (OpenAI/Ollama) ↔ Storage (Supabase)

Frontend Technology Stack: React + TypeScript + Vite

Backend Technology Stack: FastAPI + Python

  • Document Processing Pipeline
  • Dual AI Architecture
    • OpenAI Integration (Production)**
    • Ollama Integration (Privacy/Development)** -Data Security & Privacy
  • PII Protection
  • Secure Storage

💪 Challenges & Lessons Learned

Challenge 1: AI Response Consistency

  • Problem: Different AI models (GPT-4 vs Ollama) produced varying response formats, making parsing unreliable.
  • Solution: Implemented a robust response parser with multiple fallback strategies:
  • Lesson: Always build multiple parsing strategies when working with AI-generated content. AI models can be inconsistent, so your code needs to be resilient.

Challenge 2: Performance at Scale

  • Problem: Processing large credit reports (14+ sections) was taking 60+ seconds, causing frontend timeouts.
  • Solution: Implemented parallel processing with intelligent batching:
  • Lesson: Parallel processing can dramatically improve performance, but you need to balance concurrency with service limits. Batching prevents overwhelming external APIs.

Challenge 3: AI Prompt Engineering

  • Problem: Getting consistent, high-quality analysis results from AI models required extensive prompt optimization.
  • Solution: Developed a systematic approach to prompt engineering:
  • Lesson: Effective AI prompt engineering requires clear instructions, examples, and structured output formats. Iterate based on real-world results.

🔮 What's Next

Current Phase: Private Demo & Customer Collaboration

Secure Private Beta Program

  • Controlled environment: Currently operating in a carefully managed demo environment with select customers
  • Customer partnership: Working closely with early adopters to ensure sensitive financial data is handled with the highest levels of care and confidentiality
  • Data security enhancement: Implementing additional encryption layers, audit trails, and security protocols for all customer interactions
  • Feedback integration: Iterating rapidly based on real customer needs while maintaining strict privacy and security standards

Enhanced Data Protection

  • Advanced PII masking: Expanding beyond basic patterns to handle edge cases and complex document formats
  • Secure data lifecycle: Implementing automatic data purging and retention policies
  • Customer data controls: Giving users complete control over their data storage and deletion
  • Compliance monitoring: Real-time monitoring of all data handling processes

Immediate Priority: Legal Compliance & Validation

Legal Review & Certification Process

  • Comprehensive legal review: Every AI-generated dispute letter undergoes thorough review to ensure full FCRA compliance
  • Legal partnership establishment: Building relationships with consumer protection attorneys to validate dispute letter effectiveness and legal standing
  • Regulatory compliance audit: Ensuring all dispute letters meet federal Fair Credit Reporting Act (FCRA) and state consumer protection requirements
  • Documentation standards: Creating legally-vetted templates and guidelines that AI can reliably follow for consistent compliance

Legal Template Development

  • Attorney-approved templates: Developing a library of lawyer-reviewed dispute letter templates with guaranteed legal validity
  • Jurisdiction-specific compliance: Adapting letters for different state laws and regional requirements
  • Legal effectiveness tracking: Monitoring success rates of different letter types and legal approaches
  • Continuous legal updates: Staying current with changing regulations and case law

Built With

Share this project:

Updates