IBM and CAST help customers accelerate application migration and modernization

Successful modernization projects require a strong foundation to be laid down in the form a detailed and accurate Application Discovery Phase (ADP). IBM and CAST have partnered to create a powerful, AI-driven solution that cuts through the complexity of enterprise applications landscapes and accelerate migration and modernization initiatives.

ADP is arguably the most critical step in any modernization project, because it lays the groundwork for every decision that follows. Done properly, it enables teams to understand what they’re modernizing, why they’re modernizing it and how best to do it. When done poorly—or skipped altogether—the consequences can be costly, risky and far-reaching:

• Incomplete or inaccurate application inventory
• Selection of the wrong modernization strategy
• Ballooning costs and timeline
• Increased operational and security risks
• Poor stakeholder confidence

Organizations rely heavily on digital applications and it’s not uncommon for IT teams to have thousands of applications, and having complete details about thousands of applications can be tall ask.  It’s extremely common for IT and DevOps teams to face common challenges, such as:

1. Lack of visibility into application portfolios: When organizations have hundreds or thousands of applications, several of these may be undocumented, redundant or just plain obsolete. This makes it difficult to determine which apps to keep, modernize, retire or rehost.
2. Developer on-boarding and productivity issues: DevOps teams could be spending excessive time ramping up on unfamiliar codebases, leading to costly delays in modernization projects.
3. Poor understanding of complex legacy codebases: Modernizing large, monolithic applications with years of accumulated tech-debt and poor documentation is always a time-consuming job. Developers often don’t know how components interact or where to safely make changes.
4. Open source and security risks in legacy applications: Legacy apps include outdated or vulnerable open-source components, increasing security and compliance risks during modernization.
5. Cloud migration risks and uncertainty: Organizations may lack clarity on which apps are suitable for cloud migration and how much effort is involved. Cloud-readiness assessments are often manual, subjective and not exhaustive enough.

Continuous advancements in AI are rapidly proving to be a game changer for improving the application discovery phase within modernization projects. Traditional discovery methods that were done manually were time-consuming, extremely prone to errors and were highly dependent upon the knowledge of the team members in the IT & DevOps teams— knowledge that was being continuously lost due to attrition, especially in the case of legacy systems. By contrast, AI enhances discovery by making it automated, faster, scalable and significantly more accurate, enabling better-informed decisions early in the modernization journey.

1. Automated code analysis and pattern recognition: AI-enabled tools can analyze thousands of lines of code to identify architectural patterns (for example, monolith vs. microservices), code smells and technical debt, API usage and third-party library dependencies. This reduces reliance on human reviewers and surfaces issues that might otherwise go unnoticed.
2. Mapping of dependencies: AI can automatically uncover hidden interdependencies between frontend and backend components, databases and application layers, external systems and services. This helps improve accuracy of impact analysis and migration planning as teams have access to intuitive visual blueprints of complex applications.
3. Smart application classification and clustering: By leveraging machine learning, applications can be easily grouped by technology stack, or by business function, or by modernization effort, or even custom categories. AI can accelerate identification of candidates for rehosting, refactoring or retirement based on patterns learned from similar portfolios.
4. Accelerate documentation analysis with Natural Language Processing (NLP): AI can parse legacy documentation as well as in the code and other unstructured data to extract useful insights to rapidly fill gaps and to build an extensive and accurate corpus of knowledge.
5. Cloud readiness and effort estimation: AI models, trained on historical modernization projects, can estimate migration complexity, cost, time and even Cloud service alignment (for example, what services can be replaced with managed cloud offerings).

By using CAST's industry-leading technology, IBM enables clients to assess, prioritize and modernize applications with unparalleled speed and accuracy.

Key highlights of the IBM and CAST solution include:

• AI-Powered application discovery: Through CAST’s deep code analysis and application blueprinting, organizations can rapidly gain a clear understanding of their application portfolio. This leads to better decisions while reducing overall risk
• Technical debt identification and prioritization: CAST’s AI tools surface hidden technical debt, helping enterprises focus on the most impactful modernization opportunities and improve ROI.
• Smart cloud-fit assessments: Go beyond conventional cloud readiness checks - with CAST and IBM, you get precise recommendations on the best-fit cloud targets for each application.
• Microservices transformation: A proven AI-engine identifies which monolithic applications are suitable for microservices and provides actionable transformation blueprints.
• AI-augmented roadmaps and decisions: IBM leverages CAST Insights and gen AI to: a) generate smart modernization roadmaps; b) prioritize by technical health, business value and effort; c) identify cloud-fit and microservices candidates; and d) recommend targeted PaaS or containerization strategies.

Our AI-infused migration and modernization factory is a comprehensive, industrialized approach designed to help enterprises accelerate their journey to hybrid cloud and modern application architectures. It provides a scalable, repeatable framework that combines automation, AI and deep engineering expertise to assess, migrate and modernize legacy workloads.

The model includes a structured set of services such as application discovery and assessment, code refactoring, re-platforming, containerization and DevSecOps integration. It leverages IBM’s cloud-native tools, Red Hat OpenShift and our key strategic alliances with hyperscaler partners to deliver rapid and flawless modernization with minimal disruption.

The factory approach blends CAST Insights with IBM’s proven methodologies and AI-powered automation to deliver:

• Up to 50% faster cloud migration timelines
• 60% faster application discovery
• 30% reduction in modernization costs
• Fact-based, continuous modernization strategies
• Significant drop in post-migration defects and rework

The customer is one of the largest banks in USA and were in need of assessment and modernization of their mainframe landscape. The key goals were to improve time to market, enable higher levels of agility and flexibility in the business operations, and reduce operational costs and risks.

IBM deployed a solution based on IBM Consulting Advantage for Cloud Transformation (ICA4CT) and CAST Imaging, for assessing the entire application and also for analyzing the source code. The solution worked extremely well, and our team was able to reduce the assessment and code-analysis time by a factor of 60%—from several months to a just a few weeks.

The joint solution from IBM and CAST is more than a technical offering—it’s a new way of working. The solution ensures the discovery phase is not just a checkbox, but a strategic accelerator for successful, cost-effective modernization. With agentic AI-infused teams, scalable pricing models (unit-based or capacity-based) and a partner-aligned GTM strategy, it’s engineered for sustained transformation to make your cloud journey faster, more predictable and with reduced risk across the entire continuum.

The solution includes:

• Assessment: Using CAST Highlight and CAST Imaging, IBM quickly evaluates application complexity, technical debt and modernization readiness.
• Strategy: Align application portfolios with business goals to define modernization approaches - whether rehost, refactor, re-platform or rebuild.
• Execution: With IBM’s AI-infused migration factory and CAST’s visual insights, teams can modernize with precision.
• Continuous modernization: Monitor, optimize and evolve applications using CAST’s real-time analytics and AI-driven recommendations.

Ready to modernize with confidence? Let IBM and CAST blueprint your path to digital transformation.

Contact IBM Consulting