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Enterprise knowledge reconstruction first
We make the application, dependencies, rules, and target decisions explicit before asking agents to transform it.
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AI-Led Legacy Modernization
Modernize complex software without losing the knowledge the business depends on.
Overview
AI-Led Legacy Modernization uses ASIMOV, Accion Labs' AI engineering platform for enterprise software modernization, to modernize complex applications without losing the knowledge the business depends on. Rather than converting code, ASIMOV reconstructs how the system actually works, from code, data, business rules, and dependencies, then defines the target state and executes controlled transformation with traceable evidence at every step.
The Challenge
Legacy modernization is slow, expensive, and risky because the system knowledge needed to change it safely is fragmented across code, data, batch jobs, interfaces, screens, business rules, dependencies, and a small number of experienced people. Manual discovery and rewrite-heavy approaches consume significant time and cost, while code-conversion tools can generate a new stack without proving that system behavior and target architecture have been correctly understood.
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What We Deliver
- Connected source and target intelligence. We build intelligence up front to reduce manual discovery, shorten planning cycles, and avoid repeated reverse engineering.
- Governed agent support. Governed agents support documentation, readiness, planning, transformation, generation, testing, and validation, accelerating modernization while reducing engineering effort and rework.
- Documentation baseline. Function-level functional documentation is the baseline, with deeper artifacts produced where required.
How We Do It
ASIMOV treats modernization as enterprise knowledge reconstruction and controlled software transformation, not code conversion. One intelligence core supports discovery through maintenance.
Discover and document
Reconstruct the application from code, configuration, schemas, interfaces, batch assets, and available evidence, then verify the understanding.
Define the target
Capture the approved target architecture, transformation rules, retained and retired components, sequencing, and source-to-target relationships.
Engineer or migrate
Use governed agents and reusable playbooks to transform or generate code, interfaces, configurations, data objects, and tests.
Validate and maintain
Apply compilation, testing, reconciliation, traceability, exception management, and human gates, then retain the system intelligence for future change and support.
How BreezeAI Works
Model
Extract and maintain the four-layer ontology of the application: functional intent, design, architecture and code.
Ground
Give each agent the task-specific slice of the graph it needs, nothing more.
Validate
Check every proposed change against the graph, contracts, and generated tests before it lands. A failed gate blocks the merge and returns evidence to the engineer.
Accelerate
Apply the loop across the full lifecycle: coding, testing, documentation, modernization and release.
What You Get
✓
Connected source and target views of the application and transformation path
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Function-level documentation grounded in source evidence
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Modernization scope, target fitment, risk, sequencing, and work-package plans
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Generated or transformed software assets with validation and traceability where in scope
✓
Living system intelligence for future support, rationalization, convergence, and enhancement
Key Accelerators
ASIMOV
Accion Labs' AI engineering platform for enterprise software modernization and controlled software transformation.
BreezeAI
A continuous-engineering path for the live application once transformation is complete.
Business Outcomes
01
Faster modernization by reducing manual discovery, analysis, and repetitive engineering effort
02
Lower modernization cost through reusable system intelligence, automation, and reduced rework
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Reduced modernization uncertainty through explicit source and target understanding
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Lower key-person dependency through captured, reusable system knowledge
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Parallel and repeatable execution across modules and transformation waves
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A modernized application with engineering evidence and retained knowledge for what comes next
Proof Points
Modernization programs across mainframe, Java, and desktop generations show the same approach holds no matter how old or unusual the stack.
01
15M+ lines modernized. Delivered across mainframe, Java, and desktop systems, so scale is proven, not theoretical.
02
Multiple technology generations. Documented work spans Java version and framework upgrades, Delphi-to-.NET transformation, and proprietary-scripting modernization.
03
The hardest stacks included. ASIMOV program experience covers COBOL on AS400, VB.NET, Struts-era Java, and other complex enterprise systems, with customer-specific metrics shared where approved.
Why Accion
More than legacy migration
ASIMOV also supports documentation, readiness, rationalization, convergence, targeted enhancement, and maintenance.
Source-to-target intelligence
Modernization is governed through connected source understanding, approved target architecture, and a traceable transformation specification.
Evidence-led validation
Compilation, testing, reconciliation, traceability, exceptions, and human gates are selected to fit the scenario.
Delivery accountability
Accion combines the platform with engineering execution and remains accountable for the agreed modernization outcome.
Knowledge retained
The system intelligence captured during modernization remains useful for future support, rationalization, and enhancement.
Have a legacy application you need to modernize? Tell us about the system, the target direction, and the constraints that matter.
FAQs
AI-led legacy modernization is a controlled transformation approach that reconstructs an existing application, defines its target state, and uses governed AI engineering to document, plan, transform, generate, validate, and transition the system.
Yes. ASIMOV engagements can start with documentation, discovery, readiness, a proof wave, rationalization, convergence, re-engineering, or maintenance, so full modernization is one path rather than a prerequisite.
Business behavior is preserved when modernization connects source evidence, rules, dependencies, target decisions, tests, and validation artifacts, so what must stay the same and what changes on purpose can both be traced and reviewed. Accion Labs runs this through ASIMOV, with source-to-target traceability at every step.
Accion Labs has modernized more than 15 million lines across mainframe, Java, and desktop systems, including COBOL on AS400, Delphi, VB.NET, Struts-era Java, and proprietary scripting stacks. ASIMOV reconstructs each system before transformation, so the approach holds across technology generations.