LegacyShield — AI-Native Loan System Migration

Escape your COBOL prison in weeks, not years

LegacyShield automatically translates 20-year-old COBOL loan origination systems into modern Python/Node.js APIs using Claude-powered semantic parsing, cutting migration costs by 70% while maintaining TRID/ECOA compliance. Credit unions get production-ready microservices with automated risk assessments instead of $2M+ consulting rewrites that take 18+ months.

Key Benefits:

- Automated COBOL-to-modern translation using Tree-sitter parsing + GPT-4 logic mapping, eliminating 90% of manual recoding work

- Built-in regulatory compliance validation for Fair Lending, TRID, and ECOA rules with audit trails that satisfy examiners

- Kubernetes-orchestrated migration with zero-downtime cutover and automatic rollback if business logic validation fails

MVP Scope: Build an automated system that ingests legacy COBOL loan origination code, parses business logic into semantic graphs, translates to modern Python/Node.js APIs, validates regulatory compliance (TRID/ECOA/Fair Lending), and generates migration reports with risk assessment for credit unions migrating from 20+ year old mainframe systems.

Tech Stack: Tree-sitter, Claude/GPT-4, IDA Pro/Ghidra, Node.js, PostgreSQL, Docker, Kubernetes

Components:

- COBOL/Mainframe Parser Engine

- AI-Powered Logic Translator

- Compliance Validator

- Modern API Generator

- Migration Orchestrator

Quality assessment: Strong technical specificity (COBOL parsing, semantic graphs, compliance validation) and genuine market pain point (credit union legacy system costs), but artifact is incomplete (pitch text cuts off mid-sentence), lacks concrete proof-of-concept results, and doesn't differentiate sufficiently from existing migration tools or explain why LLM-based translation solves the regulatory complexity better than rule-based approaches.