Agentic AI Accelerating Discovery Phase For A Leading Financial Institution

In the midst of a legacy modernization effort, a leading financial institution aimed to streamline its SOA-based architecture built on TIBCO, beginning with a focused discovery phase to assess automation readiness.

  • Service discovery was highly manual, slowing down understanding of legacy systems
  • Inconsistent documentation practices hindered reuse and slowed collaboration
  • Developers spent significant effort on test case creation, diverting time from core implementation
  • Lack of intelligent tooling limited visibility into service dependencies and business logic
    The client wanted to lay a strong automation foundation — empowering developers with AI-driven support to accelerate modernization with precision and consistency.
  • We deployed AAVA™, our Agentic AI platform, to accelerate the discovery phase through purpose-built, domain aware Agentic AI workflows that supported both analysis and development tasks.

    Microservices Analysis Agent: Parsed microservices to identify service dependencies, endpoints, HTTP methods, request/response payloads, and core business logic

    SOA Analysis Agent: Analyzed legacy SOA components to extract database calls, SIBIS wrapper interactions, external service calls, and referenced business class files

    Documentation Agents: Assisted developers in generating detailed and standardized service documentation to support downstream engineering and reduce ramp-up time

    Unit Testing Agent: Auto-generated JUnit test cases -including positive and negative paths – for targeted services like the Journal Manager Microservice

    QE Agent: Began supporting QA teams with Rest Assured test script generation for API validation

    This Agentic AI-led approach delivered immediate value in the discovery phase — without requiring intrusive changes to existing systems.

    Trusted by Clients. Respected by Partners.

    Clients cite strong leadership, responsiveness, and reliable delivery. Partners point to engineering depth, SME coverage, and a steady focus on outcomes over activity.

    Business Impact

    By embedding intelligent AI agents into the discovery process, the client realized measurable value early -proving the viability of Agentic AI as a key enabler for their modernization roadmap.

    Achieved 50–75% time savings across microservices and SOA discovery tasks

    Reduced unit test development time by 67%, freeing developers to focus on core logic

    Cut documentation and formatting effort in half through AI-assisted wiki generation

    Delivered up to 6x acceleration in extracting service metadata, dependencies, and business logic

    Accelerated test preparation through automated unit and API test generation

    The success of this phase now positions the client to scale automation confidently across the broader transformation initiative in collaboration with Ascendion.

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