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Legacy Transformation.
Evolved.

from automated knowledge extraction to AI-powered modernization of existing systems.

In a world where technological agility determines market success, legacy systems that have grown over decades are often the bottleneck for innovation.

LegacAI is our answer to this challenge: an AI-powered solution that goes beyond mere analysis and enables the industrialized transformation of legacy estates into modern architectures.

With LegacAI, our in-house tool for automated knowledge extraction and code transformation, we systematically reduce technical debt.

By combining deterministic analysis with generative AI, LegacAI delivers high-quality, traceable output – and users can intuitively explore the functionality of existing legacy systems via chatbot and automatically migrate them to new programming languages.

Why LegacAI?

Hybrid Architecture

Conventional large language models (LLMs) often reach their limits with complex legacy code – they hallucinate or lose context in monolithic structures. LegacAI overcomes these hurdles with a hybrid architecture that combines deterministic analysis with generative AI.

From Understanding to Action

While competitors often stop at documentation, LegacAI delivers ready-to-use, modernized code (Clean Java).

System-Wide Semantics

Instead of looking at isolated code fragments, the tool derives stable semantics directly from the structure of the entire system.

Sustainable Debt Reduction

We don’t just visualize the current state – we systematically reduce technical debt through targeted knowledge extraction and incremental modernization.

Benefits of the Architecture

Greater Efficiency

With LegacAI, we accelerate modernization projects by reducing manual effort by a factor of two.

Flexibility & Interoperability

We process legacy systems written in COBOL, RPG, Natural, and Assembler alike. In addition, our architecture optimizes token costs and offers flexible LLM integration options.

Structured Workflow

Our structured workflow ensures a fully traceable modernization process by efficiently orchestrating every phase – from automated analysis and the creation and approval of requirements through to automated code generation.

Broad Stack Support

We process COBOL, RPG, Natural, and Assembler.

High-Quality Output

Generation of Clean Java code, user stories, requirements, data flows, and ER diagrams.

Flexibility

The solution supports flexible LLM integration and can be optimized for your specific environment.

Scientific Foundation

Developed by the experts at SQ Solutions, based on current research in legacy modernization

Contact

Schedule your free, no-obligation demo – see LegacAI in action on your own code.

4-Layer Pipeline

Our Modernization Process

LegacAI uses a multi-stage pipeline to ensure maximum precision and reproducibility.

The LegacAI 4-layer pipeline

Layer 1

Analysis of Heterogeneous Artifacts

We capture your source code (COBOL, RPG, Natural, etc.) and populate a highly specialized knowledge graph.

Layer 2

Multi-Retrieval RAG

By combining graph and vector retrieval, we build a deep contextual understanding of the entire system architecture.

Layer 3

Agents & Prompting

Chain-of-thought techniques and specialized AI agents extract the business logic with precision.

Layer 4

Artifact Delivery

You receive modernized code artifacts, documentation, and test cases – ready for download or for interactive exploration via chatbot.

Inside the Backend

Making Complexity Visible

  • Structure graph in LegacAI

    Structure Graph

    The structure graph refines the AST into a modernized target architecture, presented in UML format.

  • Abstract syntax tree view in LegacAI

    Abstract Syntax Tree

    The AST view presents an abstracted representation of the legacy system’s parsed and processed source code, forming the basis for further processing in LegacAI.

  • Requirements view in LegacAI

    Requirements

    The generated requirements can be reviewed, adjusted as needed, and approved.

  • Chat view in LegacAI

    Chat

    In the chat, users can ask questions to better understand the code, create flow diagrams, or review and adjust requirements. The chat offers both a planning mode and an acting mode.

  • CodeGen view in LegacAI

    CodeGen

    Automated code generation can be started based on the reviewed and selected requirements.

Who We Are

Scientific Expertise Meets Practical Experience

LegacAI is backed by the SQ Solutions team, which actively conducts research on legacy modernization and has published numerous scientific papers in the field. We combine these research findings with many years of project experience at leading banks and insurance companies.

Learn more about SQ Solutions The SQ Solutions team

Our software solution modernizes long-established mainframe systems.

With AI – structured and predictable.

Contact

Schedule your free, no-obligation demo – see LegacAI in action on your own code.