AI CoPilot Dashboard
Product Design - Internship Project
An intuitive AI-powered dashboard that simplifies workflows, offering real-time insights, smart suggestions, and action-ready tasks.
Industry
SaaS
Timeline
2 weeks
Company Name/ Client
Whatfix
Your Role
Intern
Overview
The AI Copilot Dashboard is a centralized, responsive workspace where users can interact with AI-driven suggestions, track actions, and visualize key data — all in one clean interface.
Role
Product Designer (UI/UX): Led the design system, dashboard layout, user flow optimization, and micro-interaction logic from concept to prototype.
Challenge
AI tools often overwhelm users with too much information or unclear prompts. The goal was to make AI interactions feel natural, purposeful, and user-first — not robotic or detached.
Solution
Designed a modular, intelligent dashboard that contextualizes AI suggestions within the user’s workflow. Prioritized usability, real-time feedback, and visual hierarchy to ensure clarity and control.
Outcome based on customer data collected
32%
faster task completion after integrating AI suggestions
65%
Reduction in cognitive load by simplifying multi-step processes
92%
Users found AI suggestions contextually relevant
What was the problem space?
The initial AI Copilot Dashboard faced several challenges that hindered its effectiveness:
Limited Customization: Users found the dashboard rigid, lacking flexibility to tailor views to their specific needs.
Complex Data Interpretation: Non-technical users struggled to comprehend the data presented, making it difficult to derive actionable insights.
Inefficient Dashboard Creation: Building dashboards was time-consuming, requiring manual addition of reports.
Poor Mobile Support: The dashboard was not optimized for mobile devices, affecting accessibility for users on the go.
Display Issues on Windows: On Windows systems with 150% screen magnification, the dashboard appeared oversized and sometimes illegible.
How was it impacting the business?
These issues led to decreased user engagement and satisfaction. The inability to quickly extract meaningful insights from the dashboard meant that users were less likely to rely on it for decision-making, potentially affecting productivity and the perceived value of the AI Copilot tool.
How did we uncover the actual problems to solve?
We conducted user interviews and analyzed usage patterns to identify pain points:
User Feedback: Direct feedback highlighted difficulties in navigating the dashboard and interpreting data.
Usage Analytics: Data showed low engagement rates with certain dashboard features, indicating usability issues.
What was the problem statement identified to solve?
Enhance Insight Accessibility: How might we enable users to quickly extract actionable insights from each dashboard chart?
Improve Dashboard Usability: How might we streamline the dashboard creation process and provide users with greater control over widget management?
Ensure Cross-Device Compatibility: How might we deliver a consistent and optimized user experience across various devices, including mobile and tablets?
What was the problem statement identified to solve?
Insight Accessibility: How might we empower users to quickly extract actionable insights from each dashboard chart?
Dashboard Usability: How might we improve the dashboard creation experience, providing users with greater control over widget management?
Cross-Device Compatibility: How might we ensure a consistent and optimized user experience across devices of varying sizes, including mobile and tablet?
How did we go about solving this?
1. Dashboard Creation and Customization
Flexible Grid System: Transitioned to a 12-column grid system to allow more flexible layouts.
Responsive Design: Defined minimum and maximum dashboard widths with corresponding breakpoints to ensure optimal display across devices.
2. Chart Widget Redesign
Adaptive Sizing: Implemented responsive chart sizes to maintain readability on different screen sizes.
Enhanced Hover States: Provided more detailed information on hover to aid data interpretation.
Reduced Redundancy: Eliminated repetitive event names in breakdowns to declutter the interface.
3. Windows Display Fixes
Scaling Adjustments: Optimized the dashboard for Windows' default 150% screen magnification to prevent oversized and illegible displays.
Key Learnings
User-Centered Design is Crucial: Direct user feedback is invaluable in identifying and addressing usability issues.
Flexibility Enhances Usability: Providing customizable options empowers users to tailor the dashboard to their needs, improving satisfaction.
Consistency Across Devices Matters: Ensuring a seamless experience across all devices increases accessibility and user engagement.
Attention to Detail Improves Clarity: Small changes, like improving hover states and reducing redundancy, can significantly enhance data comprehension.
