Enhancing Video Forensics
The goal was to develop a framework within an existing video forensics tool that allowed enhancement tools to be added without disrupting the current customer experience. To achieve this, I mapped existing user workflows, then iterated through several designs until arriving at a solution that met business goals, technical constraints, and customer expectations. I had approximately one month to develop working knowledge of video forensics, learn the existing application, and design the enhancements.
Two constraints of this project were:
- The feature needed to be design-ready within a month
- I was new to video forensics and wasn't familiar with the existing application
To address the constraints, I spent the first few days learning the application, its flow and UI conventions used throughout. As I worked through the application, I researched existing materials about video forensics in the field and posed questions to our internal video forensics specialists.
Key activities:
- Understanding video forensics and business requirements
- Reviewing competitor offerings and existing workflows
- Mapping user workflows
- Building an interactive prototype for feedback from internal video forensics specialists, external customers, and the development team
Understanding video forensics and the business requirements
Since I wasn't familiar with video forensics, I spent the beginning of the project researching and discussing the domain with the product manager and technical specialist. Video forensics differs from general digital forensics: while both share similar goals, video forensic examiners focus on identifying and cataloging video clips, whereas digital forensics examiners require broader skills across different case types.
Reviewing competitor offerings and understanding workflows
Once I understood video forensics workflows, we discussed the existing application flow and analyzed competitor products. This gave me ideas on how to incorporate enhancement tools organically, allowing users to modify video clips individually or in bulk.
Building the prototype
Due to limited time and lack of existing Figma components, I prototyped almost exclusively with AI. I started with a screenshot of the existing application, brought it into Figma Make to create a screen using our desktop design system, then exported it via MCP to Claude Code as a starting point to build out sections adjacent to the new enhancement tools.
The first iteration used a modal that allowed users to duplicate a video clip and apply enhancements like blur, brightness/contrast, resize, and crop, then save it as a modified clip or export to file. Since we were working with functional software, Claude could reproduce the video effects we were supporting. I completed this version in about three days.
I met with the product manager and technical specialist for feedback. This approach allowed me to validate—and in some cases correct—assumptions about how the application worked. I spent a few more days refining the design.
The second iteration was reviewed and deemed ready for internal stakeholders and developers. The reviews went well, but the modal approach conflicted with the application's UI toolkit. I worked with Claude to pivot to an inline panel design.
Next, I validated the prototype with customers. I shared access credentials with prospective customers who volunteered to review the application and facilitated usability sessions with scripted tasks. This validated our design approach and gave customers an early preview of upcoming features.
Results
Through initial research and rapid AI-assisted prototyping, we quickly iterated to a solid feature set. The working prototype allowed stakeholders and customers to interact with the design, helping us identify and resolve issues efficiently. We delivered a validated design on time, ready for development.