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Agentic AI in Software Development: A Regulated Fintech Case Study

Digital transformation in regulated industries demands more than speed: it requires precision, traceability, and the ability to move fast without introducing risk.

For fintech platforms operating in highly scrutinized sectors, the gap between a well-written user story and production-ready code can mean the difference between a competitive release and a costly delay.

fintech agentic ai case study

At a glance

  • Client
U.S.-based fintech client
  • Industry
Financial services
  • Solution Provided
IA setup for the project with custom commands / Engineering dashboards metrics
  • Technologies Used
Gorilla Logic Construct™, Claude Opus
This case study details how Gorilla Logic partnered with a U.S.-based fintech platform to automate key business analysis workflows, reduce time-to-delivery, and lay the groundwork for scalable, agentic development practices.
Understanding the client's challenges

The client is a fintech platform operating in a highly regulated financial services sector, where compliance, auditability, and delivery velocity must coexist. As the platform grew, leadership identified several compounding inefficiencies:

  • Slow delivery velocity: Manual processes for elaborating user stories and technical specifications were consuming significant engineering bandwidth and introducing inconsistency across the team.
  • Limited visibility into digital transformation progress: Without structured tooling, tracking burndown across the broader transformation initiative was difficult and largely manual.
  • Inadequate organizational metrics monitoring: Leadership lacked the real-time engineering dashboards needed to make informed decisions about team performance and delivery health.
Gorilla Logic's solution

Using Construct™, Gorilla Logic’s proprietary framework and reusable asset library, the team designed and implemented an AI-powered BA automation framework tailored to the client’s existing codebase and development workflows. The solution had two core components:

AI Setup with Custom Commands

The team built a custom AI environment anchored by a /chore command designed to generate comprehensive, implementation-ready user story specifications for new features on the client’s core payments platform. The command leverages Claude Opus with 16 allowed tools and outputs structured specification files directly into the project’s /spec directory.

A five-stage execution pipeline

Behind each command, an execution pipeline runs through five stages:

  1. Explore code: Reads documentation and searches the codebase to understand existing patterns and constraints.
  2. Query DB: Introspects the SQL schema to surface relevant tables and relationships.
  3. Web research: Gathers best practices and integration patterns from external sources.
  4. Synthesize: Consolidates findings into architecture decisions tailored to the specific feature.
  5. Write spec: Produces a full specification file ready for engineering review and implementation.
Engineering dashboard metrics

In parallel, Gorilla Logic implemented engineering dashboards giving the client’s leadership real-time visibility into delivery metrics, digital transformation burndown, and organizational performance indicators.

The Result

The impact of the engagement has been both immediate and structural:

Faster, more thorough story elaboration

Engineers and BAs now spend significantly less time writing technical specifications and test plans, with the AI doing the heavy lifting of codebase research and synthesis, so every story is grounded in a thorough understanding of the code it will touch.

Earlier risk and integration awareness

The deep analysis capability lets the team proactively identify potential database changes and risks before a single line of implementation code is written, while also reviewing external documentation to map out potential future integrations and keep everyone aligned on architectural direction.

A foundation for agentic development

Teams can now validate a proposed solution against both the technical specification and the original user story in a single automated review pass, and the tooling positions the client for the next evolution of software delivery, one where automated agents handle increasingly larger portions of the development workflow.

Ready to modernize your engineering workflows?

Gorilla Logic helps technology teams in complex, regulated environments move faster without sacrificing quality. Contact us to start the conversation.