A collection of AI applications, agents, copilots, and orchestration workflows designed to reduce repetitive work while keeping evidence, ownership, and human review visible.
Each case study separates what the system automates from the decisions and controls that remain human-owned.
Product Builder & AI Designer
Built a multi-agent product connecting document analysis, editable ROI, human approvals, and reporting.
Outcome
Delivered a working MVP with evidence-grounded recommendations and a reviewable rollout roadmap.
Release Manager
Connected Jira ticket changes to structured release updates in Slack.
Outcome
Eliminated manual status reporting for the tracked workflow while keeping Jira as the source of truth.
QA owner and creator
Built a domain-aware QA copilot that generates structured, selector-aware test cases for human review.
Outcome
Standardised test-case quality and improved the path from manual validation to automation.
Product strategy and delivery lead
Designed cross-system ticket classification and routing with traceable handoffs.
Outcome
Reduced technical-ticket resolution turnaround time by 50%.
Release Manager
Designed approval-led release controls and retained final go/no-go authority.
Outcome
Made test evidence, approvals, rollback plans, and human accountability visible before release.
Product strategy and delivery lead
Connected transcription, summaries, and action-item extraction into a reviewable workflow.
Outcome
Created a consistent record of decisions and next actions for distributed teams.
System designer and builder
Designed a policy-aware gateway, approval controls, and audit receipts for AI operators.
Outcome
Demonstrated an experimental pattern for controlled CRM automation.
Workflow designer and operator
Connected research, tailored materials, tracking, and quality checks in one human-reviewed workflow.
Outcome
Created 16 structured application workspaces with repeatable preparation and review.