AI-native legacy migration: faster, safer, finally predictable
Core banking modernization powered by intive's AI-native framework.
When your core resists change, every initiative pays the price
Financial institutions face compounding pressure: accelerating time-to-market demands, growing expectations to innovate, tightening margins, compliance requirements, and intensifying competition from digital-native players. Legacy cores sit at the center of all of it –slowing everything down, concentrating risk, and resisting change.
intive's AI-native framework was built for this reality: structured modernization that is faster at every phase, operationally safe, and built on a knowledge base that evolves with every iteration.
intive's AI-native framework was built for this reality: structured modernization that is faster at every phase, operationally safe, and built on a knowledge base that evolves with every iteration.
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How it works: intive's AI-native framework
Legacy code analysis
In a structured Discovery phase, AI interrogates legacy source code–surfacing business rules, validations, and transaction flows never formally documented.
From months to weeks,without depending on legacy experts.
From months to weeks,without depending on legacy experts.
Artifact generation
Validated rules are translated into user stories and technical tickets covering every existing use case. Engineering teams work from complete, verified specifications.
Every development decision is backed by validated knowledge.
Every development decision is backed by validated knowledge.
AI-powered frontend delivery
AI agents analyze the bank's design system, detect components from Figma screenshots, and generate production-ready code enforcing consistency and accessibility standards.
Interfaces built by AI, validated by engineers, consistent across every channel.
Interfaces built by AI, validated by engineers, consistent across every channel.
Iterative, incremental execution
Migration proceeds domain by domain. Each iteration is verified before the next begins, keeping the rest of the system stable and operational throughout.
Production-ready value at every iteration. Risk contained at every step.
Production-ready value at every iteration. Risk contained at every step.
Automated QA
QA engineers provide context and AI generates standardized, maintainable test suites. Static analysis and peer review validate every output before it moves forward.
Shorter stabilization cycles. Hidden riskcaughtbefore production.
Shorter stabilization cycles. Hidden riskcaughtbefore production.
Reusable knowledge assets
Every phase contributes to a shared knowledge catalog, enabling any developer to continue the migration efficiently and consistently from day one.
The more modules migrated, the faster the next one becomes.
The more modules migrated, the faster the next one becomes.
Trusted by leading financial institutions
“When millions of users rely daily on your systems, there is one way to migrate with confidence: understand completely before you act, deploy AI agents that automate on top of fully recovered knowledge, maintain careful human oversight at every step, and leverage what you've learned to scale.”
Claudio González
Global CTO & EVP at intive
Let's map your migration together.
Get in touch.
Embarking on an AI-native legacy migration is, at its core, an organizational shift. When agents handle legacy decoding and repetitive testing, engineers can focus on the complex problems that actually move the needle.
intive's framework is designed to help you reclaim control over your technology stack – maintaining operational stability while building the capacity to keep evolving.
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