Flezi EMT – AI-Enabled Legacy Modernization

By integrating Generative AI and Microsoft Azure capabilities, EMT enables organizations to analyze, document, refactor, and migrate legacy applications with up to 40-50% higher developer productivity, 40-50% lower AI infrastructure cost, and 30-45% reduced delivery risk compared to traditional approaches

Customer Pain Points Addressed

• High maintenance costs and dependency on legacy skillsets – outdated systems require rare expertise and high support effort.
• Incomplete documentation and knowledge loss – decades-old systems lack updated references, increasing modernization risk.
• Complex interdependencies between programs, data, and batch jobs – manual analysis slows down modernization and increases error rates.
• High risk and uncertainty in large-scale migration – traditional methods lack automation, visibility, and consistency for cloud readiness.

How FPT’s EMT Solution Addresses These Challenges

• EMT X-ray – Assessment & reverse engineering: builds asset inventory and migration strategy, and generates basic/detailed design from existing source code and documentation.
• EMT Bridge – Application & data migration: migrates COBOL/JCL/RPG to modern Java/ReactJS architectures and SAM/VSAM/DB2/IMS data to PostgreSQL, replacing IBM/Fujitsu/AS400 utilities.
• EMT Forge – Reverse & forward engineering: restructures business processes into M*-service architecture and builds new applications from AI-assisted specification and design.
• EMT vAlid – AI-powered testing: runs pattern, unit/integration, and comparison tests to validate legacy-to-modern migration outputs.
• EMT Run – DevOps & operations: builds, deploys, and scales cloud-native infrastructure (Azure/AWS/GCP) with continuous monitoring and failure prediction.
• EMT Shield – AI security gateway: masks PII and controls cost for AI/LLM calls, and scans code for security and secrets issues (SAST/SCA), independent of the AI engine.
• EMT BrAIn – The AI core connecting all EMT modules through Mentor, Co-pilot, and Worker modes, providing shared agents, an MCP server, and APIs across the modernization journey.

Outcome

• 40–50% higher Developer Productivity through AI-augmented engineering across the full modernization lifecycle.
• 30–45% lower Delivery Risk via deterministic code mapping and continuous AI-assisted validation.
• 40–50% lower AI Infrastructure Cost through governed, cost-optimized use of AI/LLM services.
• 90% of tasks fully automated with zero SME re-work needed across assessment, migration, and validation.
• ~40% total program effort reduction following FPT's unified 4R approach (Rewrite, Rebuild, Replace, Retain) with continuous governance from EMT BrAIn.