Adapts.ai Launches Generative AI Platform That Eliminates the Legacy Code Crisis, Promises Over 80% Reduction in Software Maintenance and Modernization Effort

Adapts.ai, a pioneer in applying Generative AI to enterprise software lifecycle management, today announced the general availability of its revolutionary GenAI platform, a system designed to deconstruct, document, and help modernize legacy codebases with unprecedented speed and industry-standard quality.
November 19, 2025 - Adapts.ai, a pioneer in applying Generative AI to enterprise software lifecycle management, today announced the general availability of its revolutionary GenAI platform, a system designed to deconstruct, document, and help modernize legacy codebases with unprecedented speed and industry-standard quality. The platform addresses one of the most persistent and costly challenges in modern business: the overwhelming burden of technical debt, offering a high-confidence path to modernization that can save enterprises over 80% of the effort typically expended on these projects.

More information can be found at https://adapts.ai.

The Silent Economic Crisis: The Legacy Code Drain

The global economy currently runs on trillions of lines of aging software, often poorly documented, managed by shrinking teams, and built on obsolete architectures. This technical debt isn't just an inconvenience; it is a silent, multi-billion-dollar economic crisis. Traditional software maintenance and modernization initiatives are notoriously high-risk, frequently delayed, and prone to failure, often due to one critical bottleneck: understanding the existing code.

Software engineers spend up to 70% of their time simply navigating complex, undocumented systems, tracing logic, and reverse-engineering the intentions of developers long since departed. This process, manual and error-prone, becomes the single greatest drag on innovation. Modernization projects, which aim to transition applications to contemporary languages, cloud-native architectures, and enhanced security protocols, stall because teams are forced to make high-stakes decisions based on fragmented knowledge. The cost of a failed or delayed modernization - measured in missed market opportunities, escalating security risks, and continued reliance on outdated infrastructure - is staggering.

Adapts was founded to solve this problem fundamentally. Instead of building a better compiler or a faster cloud, the company built an intelligent system capable of replicating the lost institutional knowledge of an application, acting as a digital archaeologist that extracts the core business logic from the code itself. The result is a paradigm shift: moving software maintenance and modernization from an expensive, reactive effort to a predictable, proactive, and specification-driven process.

Deconstructing Code: The GenAI-Powered Engine

The core of the Adapts' breakthrough lies in its proprietary GenAI-powered engine. This isn't a general-purpose Large Language Model (LLM); it is a highly specialized platform designed and trained exclusively on the structures, patterns, and complexity of enterprise codebases. The process begins by connecting to the client's existing code repository, where a suite of AI Agents is deployed to perform a deep-scan, multi-layered analysis of the entire codebase.

The engine doesn't merely translate comments or identify functions; it reverse-engineers the complete application logic. It meticulously reconstructs the relationships between components, the flow of data, and the underlying business rules that the code enforces. This granular deconstruction is what enables the platform to confidently drive the subsequent modernization. By establishing a complete, verified understanding of the "what" and "why" of the legacy system, Adapts ensures that the resulting modernization execution can meet all critical requirements: no compromise on business and technical specifications, and no loss of sight concerning modern architecture and security.

This comprehensive approach is why Adapts is achieving unparalleled efficiency gains. The promise of saving over 80% effort is realized by eliminating the vast majority of manual discovery, documentation, and logic-tracing work that currently consumes engineering teams. It allows highly paid, skilled developers to shift their focus from deciphering relics to building the future.

Feature Deep Dive: Code to Wiki - The Revolution in Documentation

The first, and arguably most foundational, component of the Adapts platform is Code to Wiki. This feature transforms a complex, undocumented codebase into a comprehensive, human-readable, and up-to-date knowledge base - a single source of truth for maintenance and modernization teams.

The AI Agents generate high-fidelity documentation that goes far beyond simple API references. The output is a complete, dynamic wiki featuring:

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Detailed Specifications: A plain-language breakdown of the domain-specific logic and functionality embedded in the code, translating complex, cryptic programming constructs into clear business rules.

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Architectural Visualizations: Automated, current diagrams illustrating the application's architecture, including component dependencies, microservice layouts, and deployment topology.

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Sequence Diagrams: Visual representations of how different parts of the application interact during a typical operation, clarifying complex process flows that were previously only discernible through painstaking code tracing.

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Entity Relationship Models (ERMs): Clear diagrams of the underlying data structures, showing how critical business entities are stored and relate to one another.

This wiki is not a static artifact. For applications undergoing regular changes, Adapts can be configured to periodically re-scan the codebase or integrate with CI/CD process with every code merge, ensuring the wiki is always up-to-date. This living documentation dramatically minimizes code ramp-up time for new team members and streamlines troubleshooting for existing engineers. When a bug fix or feature enhancement is needed, the required context is immediately available, leading to maximum efficiency in day-to-day maintenance. The ability to consume this detailed wiki, often supported by an integrated AI assistant, provides unparalleled context awareness to the engineering team. Furthermore, the platform is built to handle large code repositories with thousands of files, scaling to the needs of the largest global enterprises.

Modernization with Confidence: Generating the Future

Once the Code to Wiki foundation is established, the platform moves to the requirements generation phase: Modernization with Confidence. This capability eliminates the risk associated with traditional modernization, which often involves manual discovery process of features in the legacy codebase constantly referring back to an incomplete understanding of the legacy system.

With the detailed specifications and diagrams as the certified blueprint, the Adapts engine can automatically generate the requirements for the modernized application code. The confidence comes from the complete coverage of requirements while enabling human-in-the-loop setup to validate the modern stack feature set.

This specification-driven generation capability is the key to achieving blazing fast turnaround times. By automating the build process based on an exhaustive, trusted set of requirements, projects that once took years and involved complex, multi-million dollar contracts can be completed in a fraction of the time. This fast-track capability is crucial for organizations looking to quickly migrate off outdated platforms to enhance scalability, security, and cloud readiness.

Addressing Enterprise Liability: IP Protection and Secure Innovation

A critical barrier to enterprise adoption of Generative AI for code is the potential legal risk and IP liability associated with generated code. Many general-purpose LLMs are trained on vast, public datasets, raising concerns about intellectual property leakage or replication of copyrighted material. Adapts has engineered a solution that directly mitigates this risk.

The platform ensures IP protection by prioritizing the generation of custom, original code. Its specialized LLM engine is architected to deliver unique, optimized solutions that are derived from the logic in the client's proprietary wiki specifications, rather than direct replication or synthesis of external code snippets. This rigorous methodology ensures that the generated code is free from common IP risks, providing enterprises with the security needed to embrace AI-driven innovation responsibly. Users can trust that their codebases, whether the reverse-engineered wiki or the newly generated application, are secure within Adapts' robust systems and processes, protected by enterprise-grade data security protocols.

Moreover, the platform recognizes that AI generated apps need maintenance too! Unlike simple one-time translation tools, Adapts' advanced context awareness remains an active part of the software lifecycle. Should the business application require ongoing maintenance-addressing new vulnerabilities, ensuring reliability, or delivering updates-the platform minimizes the time and effort involved. The continuous, contextual understanding of the code makes troubleshooting straightforward and simplifying enhancements for maximum long-term efficiency.

Trusted Leadership and The Future of Software Engineering

Adapts is already trusted by leaders that prioritize efficiency and recognize the strategic necessity of modernizing their digital foundations. By empowering software engineering teams with intelligent AI solutions, the company is not just fixing legacy systems; it is fundamentally elevating the role of the engineer. Instead of being code archaeologists, developers become architects, focusing on high-level design, innovation, and direct business value creation.

The launch of the Adapts platform marks a watershed moment, making true, high-confidence application modernization accessible and predictable for every enterprise, regardless of the size or age of their code repository.

About Adapts

Adapts is the product of VerifyAI, Inc., a company dedicated to leveraging Generative AI to solve the most difficult challenges in enterprise software engineering. The Adapts platform is a GenAI engine that deconstructs existing application code into comprehensive, verified specifications and diagrams, enabling confident, fast-track modernization and effortless ongoing maintenance. The company is committed to industry quality standards, IP protection, and empowering software teams globally.

Visit https://adapts.ai for more details.

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