Modernizing IT Systems—Agent-Based, Structured, and Controllable

Assessment modernization with AI

Do you want to modernize your IT landscape without turning it into an unmanageable large-scale project? In our assessment, we provide clarity on code, dependencies, and risks—and show where AI and agent-based workflows can truly help in your specific context. You’ll receive options for action, a well-founded recommendation, and an actionable roadmap for a structured start.

When Legacy Systems Become a Strategic Risk

Business-critical applications often run on system landscapes that have evolved over time. They support day-to-day operations – but at the same time, risks and costs are rising:

  •  Changes become time-consuming and require extensive testing, while time-to-market decreases
  • Maintenance, operating, and licensing costs rise
  • Specialists in legacy technologies are becoming scarcer
  • Knowledge is embedded in the code – and is difficult to transfer

Modernization is therefore not just about technology. It is a strategic decision to secure your long-term flexibility.


Why Modernization Works Differently Today

In the Past

  • Manual code analysis, a lot of gut instinct
  • Uncertain effort estimates
  • Migration as a high-risk project (Big Bang, long freeze phases)

Today

  • Automated inventory of code, dependencies, and hotspots
  • Data-driven effort and risk assessment
  • Agent-based support for analysis, transformation, testing, and documentation
  • Iterative modernization with measurable quality gates

AI does not replace architectural and product decisions. But it can help you understand faster, transform more cleanly – and identify risks earlier.

    Reach a Well-Informed Decision with Our Assessment

    Do you want to modernize your tech landscape but don’t know where to start? That’s exactly what this assessment is designed for. We provide a comprehensive overview (systems, interfaces, operational realities) and use it to identify concrete modernization paths. A thorough assessment provides confidence in decision-making and reduces risk.

    Here’s how the assessment works

    In X days, we’ll work together to determine where you stand, what modernization options are available, and how to implement them step by step.

    1) KickoffGoals, Scope, Definition of “Done”
    • What decisions need to be made following the assessment?
    • Which systems/teams are included in the scope (and which are intentionally excluded)?
    2) DiscoveryInterviews + Artifact and Code Reviews
    • Interviews with tech, product, operations, and security/compliance teams (depending on the context) to clarify modernization needs, technical details such as the platforms or databases used, and the legal framework
    • Review of architecture and operations artifacts, CI/CD, monitoring, documentation, and the backlog
    • Automated inventory (where possible)
    3) AnalysisRisks, Dependencies, Options
    • Organize modernization options (and identify hard dependencies)
    • Classify the use of agents and AI appropriately: benefits, limitations, prerequisites
    4) Results WorkshopDecision Memo + Roadmap
    • Options & Recommendations
    • Prioritization and 90-Day Plan
    • Next Steps (Internally or with Us)

    What You’ll End Up With

    • Inventory & Structural Overview of your codebase and system landscape (scope, dependencies, critical paths)
    • Complexity and Risk Analysis, including hotspots and cost drivers
    • Options & Recommendations: 2–3 modernization paths with clear trade-offs (time/cost/risk/organization)
    • AI-ready guidelines: Rules, governance, and quality requirements to ensure the scalable use of AI
    • Milestone-based roadmap (prioritized, actionable, 90-day launch including quick wins)
    • Management summary (actionable, understandable, transparent)

    Agent-Based Modernization: What Does That Mean in Practice?

    Agent-based workflows are repeatable process chains that support modernization steps—traceable and controllable, e.g.:

    • Understanding code (dependencies, patterns, hotspots)
    • Preparing and documenting transformations
    • Improving tests and identifying gaps
    • Automating old/new comparisons and quality checks
    • Accelerating knowledge transfer (documentation, decision logic)

    Governance is part of the assessment: We clarify which data/artifacts can go where, which tooling and model setups are possible, and how you can ensure traceability.

    Taking a Structured Approach to Modernization

    Legacy modernization doesn’t have to be an unmanageable large-scale project. With thorough analysis, agent-based support, and clear governance, it becomes a manageable program.

    Select contact

    Dr. Xenija Neufeld

    Principal & Community-Leader
    Your contact for the topics of data science and machine learning
    Xenija Neufeld Zitat