The Business Challenge
The business situation the organisation faced before the project began.
Craft hobbyists often manage project notes, stitching progress, WIP (Work In Progress) goals, materials, and pattern-related information across scattered entries. Finding previous decisions, project context, or specific notes manually can slow down planning and reduce consistency across long-running projects.
How the Solution Was Delivered
Discovery, design, development, testing and rollout — the journey, not the tooling.
- 1Mapped the stitching project workflow and common lookup needs
- 2Built the project tracker frontend for sessions, WIP goals, and statistics
- 3Created a backend for storing project entries and reference content
- 4Added an AI assistant using retrieval-based search over stored knowledge
- 5Connected project data and documentation into a searchable knowledge layer
- 6Tested the assistant with common project and stitching-related questions
Business Outcomes & Impact
The measurable outcomes from the underlying AI Deployment — with the story behind them.
Estimated 50–70% faster retrieval of project context compared with manual note searching. Estimated time saved is around 5–10 minutes per lookup session, depending on the amount of project history involved.
Business Outcome Categories
The story behind the numbers
The solution centralizes stitching project knowledge and makes it easier to retrieve useful information without manually searching through notes. It supports faster project review, better continuity across WIP projects, and more organized hobby tracking.
Lessons Learned
What surprised the team, what worked well, and what would be done differently.
- RAG is most useful when the knowledge source is narrow and personal
- Good project structure matters more than simply adding AI chat
- Users need answers grounded in their own data, not generic AI responses
- AI assistants work best when paired with clear tracking and history features