Reimagining identity profiles with AI-driven insights to accelerate threat investigation.
Client
Red Canary
Shipped
Q3 2025
Tags
Total refactor
Design Strategy
Project summary
I led the redesign of Red Canary’s Identity Profiles, introducing actionable insights powered by generative AI and a modernized user experience. The update strengthened customer retention and gave us a significant competitive edge in a previously stagnant area of UX.
My role
Owned full design process: research, ideation, prototyping, and handoff.
Collaborated with product and engineering to ensure feasibility and alignment with broader identity revamp.
Advocated for forward-thinking features and improved overall user experience.
The problem
Our original Identity Profiles were flat-out boring. Customers found them unhelpful, and compared to competitors’ identity management tools, we were falling behind in both functionality and customer perception. We’d lost key opportunities to win on renewals because customers needed a more powerful and intuitive identity product.
Core pain points
Loss of business due to lack of feature competitiveness.
Customer complaints that Identity pages were unhelpful, leading to churn.
The solution
Focus on surfacing actionable insights rather than raw data:
Benchmarked competitors
Embedded GenAI to summarize and contextualize identity activity
Prioritized clarity and actionability over exhaustive detail
How we solved it
5 Months
Design phase
6
Major iterations
1
Design team size
Competitive Benchmarking
I started by thoroughly exploring “who the teams to beat were,” reverse-engineering their flows, and documenting patterns we could adapt or avoid.
This initial benchmarking gave us a clear north star of what features had to be included to meet customer expectations—and what we could skip for now.
Designing & Prototyping
I created low-fidelity prototypes to validate our direction early and avoid spinning cycles. Once we validated direction through stakeholder and pilot feedback, I transitioned to high-fidelity designs.
A major addition here was embedding GenAI functionality to provide quick, actionable identity insights directly in customer dashboards and threat timelines.
Customer-Driven Validation
Throughout the process, we collected customer feedback and iterated heavily on our prototypes, making small but impactful changes along the way. A tiered rollout with pilot customers allowed us to gather critical data on usability before full-scale launch.
Customer impact
Delivered parity with competitors and introduced AI-driven insights.
Reduced analyst time spent correlating threats by ~15%, enabling faster decision-making.
Set a foundation for future identity management UX enhancements.
Lessons learned
When using GenAI to provide insight, keep the information concise and impactful.
Phased releases can help get the MVP out sooner and are a great tool to get early, continuous feedback from early users.