Product thinking & digital workflows
NoteDigitize
A student-focused product for converting handwritten notes into editable text, with a workflow covering image upload, transcription review, organisation and export.
Product concept, requirements, workflow and interface direction; AI-assisted development, troubleshooting and refinement
Inside this case study 7 sections
The problem
I prefer writing notes by hand because it helps me process what I’m learning. The challenge was keeping physical notes organised while making them easier to find and use later.
NoteDigitize started with a practical goal: upload my handwritten notes and send the text into Notion. I expanded the workflow to support other destinations, with students as the main intended audience.
My contribution
I defined the product, planned its workflow and interface, and translated those decisions into instructions for AI-assisted development. I reviewed, troubleshot and refined the implementation, retaining responsibility for what to build and what needed to change.
My work included planning and visualising the interface, researching tools that could support development, considering security and improvement needs, and asking student friends for feedback. AI contributed substantially to the code, under my direction.
The product workflow
The walkthrough shows NoteDigitize moving from a handwritten image to an editable transcript, then into export and note-management steps.
- Capture. Upload an image of handwritten notes.
- Review. Compare the image and transcript side by side, with a cleaned-image view available.
- Refine. Edit the text and review formatting before using the output.
- Move it into the workflow. The recording demonstrates document and note-export steps, including Google Docs and Notion views.
- Return to the work. A history view makes earlier notes accessible again.
Product decisions visible in the demo
The product begins with the workflow I actually needed: handwriting first, organisation afterwards. Side-by-side review keeps the original note visible while the user checks the extracted text. History and export options make the result useful beyond a single upload.
The guided tutorial, connection settings and help support the surrounding tasks: getting started, choosing a destination and returning to earlier notes.
The connections screen distinguishes connected destinations from export-file options and destinations that are not connected. Those interface states should not be treated as proof that every integration works end to end.
Extending the product
The refinement tool uses the OpenAI API. NoteDigitize also has its own API, providing a route for other products and workflows to access its functionality. An iOS Shortcut is a potential future integration, not one completed as part of this project.
Current status
The core product is working. Further refinement is underway before I describe it as fully production-ready. Student friends have provided feedback; this is informal product feedback, not a claim of a measured user study or commercial adoption.
What the demonstration supports
The video supports the workflow shown on screen. It does not establish transcription accuracy across a wider dataset, paying customers, user adoption, revenue or a measured saving in time.