Outcome in Numbers

AI ready applications at scale

20%

lower delivery costs and reduction in avoidable IT spend 

40%

lower cost of change across delivery and operations 

6-10

weeks go-live window

Solutions

Turning legacy applications
into AI-ready systems 

AI-driven application modernization services that reduce technical debt,
clarify intent, and enable safe enterprise AI agent integration.

Application modernization
and AI readiness assessment

  • Inventory applications, architecture, and dependencies 
  • Identify technical debt, dead code, and duplication 
  • Generate specifications and documentation from code 
  • Define AI-ready target architecture 
  • Deliver a prioritized modernization roadmap 

Spec driven code
modernization

  • Convert legacy behavior into clear, testable specifications 
  • Reduce ambiguity during refactor and migration 
  • Improve confidence through validation and testing 

Architecture refactor
and modernization 

  • Modernize application structure for modularity and APIs 
  • Improve integration patterns and system boundaries 
  • Prepare platforms for AI-driven workflows 

Code cleanup, migration,
and refactor execution 

  • Remediate high-impact technical debt 
  • Migrate or refactor languages and frameworks 
  • Strengthen testing and CI CD pipelines 
  • Plan and execute production cutover 

AI agent enablement
and governance 

  • Implement secure integration and access controls 
  • Enable audit logging and observability 
  • Apply operational guardrails for enterprise risk 
Why Gruve

Application Modernization expertise 
aligned to AI agents 

Built for practical
AI adoption 

Gruve pairs application modernization with the real operational requirements of enterprise AI adoption, including security, governance, and operational excellence.

Domain deep
modernization expertise 

Our teams combine deep application engineering experience with agentic AI expertise to modernize systems that support mission critical business workflows.

Structured for enterprise
and audit requirements 

Modernization efforts follow structured, defensible practices that improve auditability, security posture, and long-term maintainability.

FAQs

1. What is AI ready application modernization? 

AI ready application modernization prepares code and architecture, so applications are clean, modular, observable, and secure enough to support AI agents acting across enterprise systems.

2. Why do AI agents struggle with legacy applications?

Legacy applications often lack clear interfaces, reliable data access, and governance controls, making AI behavior unpredictable and risky.

3. How quickly does application modernization for AI deliver results?

Most organizations see measurable improvements within 2 to 4 weeks after assessment, with full modernization cycles completed in 6 to 10 weeks.

4.Do we need to rewrite all applications to become AI-ready? 

Yes. Gruve uses policy-controlled automation, human approvals, and full auditability to ensure governance and compliance.

5. How does this reduce long term cost? 

By eliminating technical debt and clarifying application behavior, every future change becomes faster, safer, and less expensive.

Unlock your true
speed to scale 

Enable scalable, secure, and measurable AI execution in production.