Legacy software modernization moves from slow audits to AI code analysis
Legacy software modernization is the process of understanding, restructuring, and upgrading long‑running business applications so they remain secure, compliant, and maintainable without disrupting core operations. For many large enterprises, this means untangling millions of lines of COBOL, PL/SQL, Oracle Forms, PowerBuilder, or RPG code that have powered mission‑critical systems for decades. These codebases often outlive the engineers who built them, leaving teams to maintain opaque systems with incomplete documentation and high operational risk during every enterprise system upgrade. Manual discovery and documentation can take months and still miss hidden dependencies. AI code analysis is starting to change that equation by scanning source code and documentation to build a living map of how systems behave. Startups such as Kodesage are turning that map into software maintenance tools that reduce risk and cost when modernizing aging applications.
Kodesage raises funding to scale AI for legacy modernization
Kodesage, founded in 2024 by Gergely Dombi, Miklos Szurdi and Gyorgy Szilagyi, has raised USD 6.6 million (approx. RM30.4 million) in a seed round led by VentureFriends, with participation from Portfolion and angel investors including xAI co‑founder Christian Szegedy and footballer Mario Götze. The startup builds an on‑premise AI platform focused on legacy software modernization for sectors such as banking, insurance, energy, transportation, telecommunications and the public sector, where core systems still run on decades‑old technology. Its platform performs AI code analysis on both modern and legacy stacks, automatically discovering codebases, generating documentation, and creating tests to support safer enterprise system upgrades. According to Kodesage, the goal is to help organisations "modernise faster, reduce operational complexity and improve support through AI‑assisted tooling" while maintaining control over sensitive data.
Inside the AI platform: from knowledge layer to software maintenance tools
Kodesage’s platform extracts information from source code and existing documentation to build a continuously updated knowledge layer that sits on top of legacy systems. This knowledge layer underpins software maintenance tools that can explain system behavior, suggest context‑aware code conversions, and auto‑generate tests to validate changes. The platform supports technologies including Oracle Forms, PL/SQL, COBOL, PowerBuilder and RPG, which remain common in financial and public infrastructure. By automating codebase discovery and documentation generation, AI code analysis sharply cuts the manual effort needed before a major enterprise system upgrade. AI‑assisted production support helps teams troubleshoot incidents faster, even when original system experts have retired. Kodesage’s long‑term vision is to move toward “self‑healing enterprise applications capable of continuously learning, testing and validating improvements with human oversight,” turning modernization into an ongoing capability instead of a one‑off project.
Compliance, data control and the rise of on‑premise AI
Regulated industries face a tough trade‑off: they need AI‑driven legacy software modernization, but they must keep sensitive data under strict control. Kodesage addresses this by running entirely inside customer‑controlled environments, whether on‑premise, in a virtual private cloud or in fully air‑gapped deployments. Source code, databases and business‑critical information never leave the organisation’s infrastructure, which helps meet data residency and regulatory requirements while still taking advantage of advanced software maintenance tools. This design matters for banking, insurance and public sector systems that cannot move to consumer cloud AI services. It also helps enterprises modernize in phases: legacy and new systems can coexist for years, with AI code analysis tracking dependencies between both. As institutional knowledge erodes, such embedded AI platforms become a way to preserve system understanding without breaching compliance rules.
A growing market for intelligent legacy system solutions
The expansion of Kodesage’s go‑to‑market efforts across the US and Europe signals rising demand for intelligent legacy system solutions. Enterprises are under pressure to modernize core platforms to meet security standards, integrate new digital channels and support cloud‑native services, yet they cannot afford prolonged downtime or failed migrations. AI‑driven legacy software modernization offers a middle path: augment existing teams with automated analysis, documentation and test generation to reduce upgrade risks. As more organisations adopt AI code analysis for their enterprise system upgrades, modernization shifts from a rare, high‑risk event to a managed, iterative practice. For startups in this space, the opportunity lies in converting hard‑won insights about old code into reusable platforms that scale globally. For enterprises, it promises a way to extend the life of critical systems while preparing for the next generation of applications.
