IntelliVoc | Redesigning an AI-Powered Survey Platform
IntelliVoc | Redesigning an AI-Powered Survey Platform
IntelliVoc | Redesigning an AI-Powered Survey Platform
B2B SaaS
B2B SaaS
Dashboard Design
Dashboard Design
Web Application
Web Application
Timeline
Timeline
2-3 Weeks
2-3 Weeks
Team
Team
Me & Product manger
Me & Product manger
Company
Company
AionOS
AionOS
01
Project Overview
Project Overview
Intellivoc is a comprehensive web-based survey management platform that leverages AI to simplify survey creation, distribution, and analysis.
Intellivoc is a comprehensive web-based survey management platform that leverages AI to simplify survey creation, distribution, and analysis.
Mission
Mission
Transform an AI-generated prototype dashboard into a production-ready interface with a professional design system and intuitive user flows.
Transform an AI-generated prototype dashboard into a production-ready interface with a professional design system and intuitive user flows.
Analytics Focus
Analytics Focus
Replace placeholder visualizations with meaningful, actionable data displays that help managers make informed decisions.
Replace placeholder visualizations with meaningful, actionable data displays that help managers make informed decisions.
02
The Challenge
The Challenge
The existing dashboard was functional but lacked professional polish and clear user guidance.
The existing dashboard was functional but lacked professional polish and clear user guidance.
Design Issues
Design Issues
No established color system or typography hierarchy
No established color system or typography hierarchy
Inconsistent component design and spacing
Inconsistent component design and spacing
Irrelevant placeholder visualizations
Irrelevant placeholder visualizations
Confusing information architecture
Confusing information architecture
UX Gaps
UX Gaps
Complex survey creation without guidance
Complex survey creation without guidance
Unclear survey status distinctions
Unclear survey status distinctions
Participant management needed streamlining
Participant management needed streamlining
No intuitive response analysis
No intuitive response analysis
Constraints
Constraints
Limited user research data
Limited user research data
Platform not yet live
Platform not yet live
Design decisions based on best practices
Design decisions based on best practices
03
Style Guide
Style Guide
A comprehensive Style Guide built from scratch to ensure consistency and scalability.
A comprehensive Style Guide built from scratch to ensure consistency and scalability.
03
Design Showcase
Design Showcase
Visual transformation from AI-generated prototype to production-ready interface.
Visual transformation from AI-generated prototype to production-ready interface.
05
Key Design Solutions
Key Design Solutions
Strategic design interventions that transformed the user experience.
Strategic design interventions that transformed the user experience.
Dashboard Redesign
Dashboard Redesign
Created a hero metrics section with KPIs, status-based organization, activity timeline, and 6-month trend visualization for instant insights.
Created a hero metrics section with KPIs, status-based organization, activity timeline, and 6-month trend visualization for instant insights.
AI Survey Builder
AI Survey Builder
Conversational interface that generates complete surveys from natural language descriptions, reducing creation time from 30+ minutes to under 5.
Conversational interface that generates complete surveys from natural language descriptions, reducing creation time from 30+ minutes to under 5.
Analytics Suite
Analytics Suite
Comprehensive analytics with completion funnels, device breakdowns, response timelines, and drill-down capabilities for individual responses.
Comprehensive analytics with completion funnels, device breakdowns, response timelines, and drill-down capabilities for individual responses.
Participant Management
Participant Management
Dual input system supporting both CSV imports for large-scale research and manual entry for small teams with real-time validation.
Dual input system supporting both CSV imports for large-scale research and manual entry for small teams with real-time validation.
Question Types
Question Types
Designed 6 distinct question types (paragraph, MCQ, checkboxes, dropdown, rating, linear scale) with clear visual states and editing feedback.
Designed 6 distinct question types (paragraph, MCQ, checkboxes, dropdown, rating, linear scale) with clear visual states and editing feedback.
Preview Modes
Preview Modes
Multiple survey preview options (all questions vs. one-per-page) allowing creators to test the respondent experience before publishing.
Multiple survey preview options (all questions vs. one-per-page) allowing creators to test the respondent experience before publishing.
06
Design Process
Design Process
A structured approach from research to final delivery.
A structured approach from research to final delivery.
07
Impact & Outcomes
Impact & Outcomes
Projected improvements based on industry benchmarks and competitive analysis.
Projected improvements based on industry benchmarks and competitive analysis.
30%
30%
Reduction in Survey Creation Time
Reduction in Survey Creation Time
25%
25%
Improvement in Completion Rates
Improvement in Completion Rates
40%
40%
Faster Data Analysis
Faster Data Analysis
Learnings
Learnings
Working with Constraints
Strong foundational research (competitive analysis) and adherence to established UX patterns can compensate for lack of direct user feedback when necessary.
Design Systems
Investing time upfront in design system architecture pays dividends as products scale. Component-based design with clear tokens ensures consistency.
AI Integration
AI features must be transparent, controllable, and clearly scoped to build user trust. Position AI as a copilot, not a replacement for human control.
Working with Constraints
Strong foundational research (competitive analysis) and adherence to established UX patterns can compensate for lack of direct user feedback when necessary.
AI Integration
AI features must be transparent, controllable, and clearly scoped to build user trust. Position AI as a copilot, not a replacement for human control.
Design Systems
Investing time upfront in design system architecture pays dividends as products scale. Component-based design with clear tokens ensures consistency.
Working with Constraints
Strong foundational research (competitive analysis) and adherence to established UX patterns can compensate for lack of direct user feedback when necessary.
AI Integration
AI features must be transparent, controllable, and clearly scoped to build user trust. Position AI as a copilot, not a replacement for human control.
Design Systems
Investing time upfront in design system architecture pays dividends as products scale. Component-based design with clear tokens ensures consistency.
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Like What You See?
©
Rajnish Kumar
2026
Like What You See?
©
Rajnish Kumar
2026
Like What You See?
©
Rajnish Kumar
2026
Like What You See?
©
Rajnish Kumar
2026