nightfall ai
dashboard revamped
Great products must evolve with their users, so we revamped the $40M dashboard
Year started
2025
type
solo work
Category
dashboard
mvp timeline
on going
BACKGROUND
Three years ago, the team & I designed the original Nightfall Security Dashboard, which helped secure $40M in funding by showcasing our product’s impact. Since then, our product suite has grown, and the dashboard can no longer deliver the depth of metrics today’s users need.
MY ROLE
I owned the end-to-end design process, from research and concepting to prototyping and developer handoff. It is a still on going project with many phases.
Goals
We are hoping to improve users' ability to identify security risks quickly.
Will enhance perceived value for enterprise clients during renewal discussions.
We can also position the dashboard as a competitive differentiator in sales demos.
The original dashboard succeeded in showcasing Nightfall’s core capabilities, but after three years:
Limited Metrics - Users wanted visibility into more granular and cross-product security metrics.
Static Layout - The dashboard was designed for a smaller feature set and lacked flexibility to support new product lines.
Scalability Issues - Adding new data visualizations required significant engineering effort.
The business goal was clear: redesign the dashboard to support Nightfall’s growing product portfolio while improving usability and accelerating feature delivery.
I approached this project with a clear balance between usability, scalability, and technical feasibility. Every design decision was intentional, grounded in user research, and aimed at delivering measurable outcomes for both customers and the business.
1) research & discovery
Stakeholder Interviews: Gathered feedback from Sales, Customer Success, and Product on dashboard shortcomings.
User Research: Conducted interviews with enterprise customers to understand their workflows, reporting needs, and pain points.
Data Audit: Collaborated with data engineering to inventory all available security metrics and determine integration feasibility.
2) Defining Success criteria
From research, I established the following goals for the redesign:
Expand metric coverage from ~20 core KPIs to over 50, spanning multiple Nightfall products.
Reduce time-to-insight by surfacing key metrics and trends within three clicks.
Enable modular scalability, allowing new data sources and visualizations to be added with minimal engineering overhead.
3) design exploration
I explored multiple data visualization approaches, balancing clarity, accessibility, and performance to help users quickly understand complex data. I then designed different modular, widget-based system that prioritizes the metrics most relevant to test different layouts, based on our Twilight Design System.
I also added thoughtful interaction details, including empty states to guide users when no data is available and dynamic tooltips that surface contextual information when hovering over metrics, enabling deeper insights without cluttering the interface.
4) interation & testing
Leveraging the modular components I designed, I experimented with numerous layout variations, making it easy to rearrange and prioritize the most important metrics for different user workflows.
I refined the visual hierarchy to emphasize high-risk alerts, trending violations, and urgent anomalies, ensuring users could quickly identify what mattered most. Throughout the process, I validated design feasibility with engineering, confirming that these flexible layouts could be implemented at scale without compromising dashboard performance.
Scalability is critical for data-heavy products: By designing a modular, widget-based architecture, we future-proofed the dashboard for new metrics and product lines without introducing design or engineering bottlenecks.
User context drives dashboard effectiveness: Role-based views ensured that analysts, managers, and executives each see the metrics most relevant to their decisions.
Early collaboration accelerates delivery: Involving engineering, data, and customer-facing teams from the start reduced rework and ensured alignment on both technical and business goals.
Data design must balance clarity and depth: Visual hierarchy and clear labeling helped simplify complex security data while preserving detail for power users.
This project is still ongoing as we continue to roll out additional metrics, refine visualizations based on user feedback, and optimize performance for large-scale enterprise deployments.
