AI-Enabled Enterprise Workflow Platform

connected stages, from raw context to test code

tools in one toolchain: Confluence, JIRA, Figma, draw.io, GitHub Copilot

publishing to Confluence and JIRA

Context

This project was the redesign of an AI-powered project assistant built for banks. It is an intelligent assistant that helps teams generate business requirements, create business cases, design architectures, develop UI/UX designs and write test cases, all powered by AI.

Bank product teams work across meeting transcripts, emails, requirements documents, backlogs, design tools and development environments. Moving information between these stages fragments the workflow and creates repeated manual effort.

The challenge

How might teams move from unstructured project information to the documentation, backlog, designs and tests they need to start delivery, without recreating and transferring information by hand across many tools?

The experience

A connected workflow from first project context through to development and testing:

• Capture context: start from meeting transcripts, emails and notes
• Generate requirements: turn project information into business requirements and business context documents (BRDs and BCDs)
• Structure delivery work: generate JIRA epics and user stories
• Support design: connect the workflow to UI/UX artefacts and diagrams
• Prepare for testing and development: generate test cases and support development and test-code workflows
• Connect the toolchain: integrate with Confluence, JIRA, Figma, draw.io and GitHub Copilot, with one-click publishing to Confluence and JIRA after setup

What I did

I redesigned the app around how people move through the end-to-end workflow and work across connected tools. The design had to make a multi-stage process easy to follow, bringing documentation, backlog creation, design and testing into one coherent experience.

Why it matters

The platform shortens the distance between understanding a project and having the artefacts needed to deliver it. Instead of treating AI as a standalone chat feature, it connects AI-generated outputs to the tools and processes teams already use.