Project Overview
Indigenius is a multi-channel AI agent platform developed by Cdial.ai that enables businesses to automate workflows across email, chat, SMS, and voice channels. As the lead product designer, I was responsible for creating an intuitive interface that made complex AI automation accessible to non-technical users.
The platform allows users to build, deploy, and manage AI agents that handle customer inquiries, process requests, and complete tasks without human intervention—all while maintaining natural, context-aware conversations across different communication channels.
This case study demonstrates my ability to design complex enterprise software, conduct user research, iterate based on data, and deliver measurable business impact.
Key Responsibilities
Led end-to-end design process from research to final implementation
Conducted user research with 45+ potential customers across 3 industries
Created design system with 120+ components for consistency
Collaborated with 8 engineers and 2 product managers in agile sprints
Ran 23 usability testing sessions with iterative improvements
Designed for accessibility (WCAG 2.1 AA compliance)
The Problem
Small to mid-sized businesses were drowning in repetitive customer communication tasks across multiple channels, but existing automation tools were either too complex for non-technical users or too limited in functionality.
Tool Complexity
78% of users found existing automation platforms too technical and difficult to set up
Channel Fragmentation
Teams managed 4-7 different tools for email, chat, SMS, and voice support
Time Waste
Support teams spent 22.5 hours/week on repetitive, automatable tasks
Context Loss
64% of customer conversations lost context when switching channels
Problem Statement
"How might we create an AI automation platform that is powerful enough to handle complex multi-channel workflows, yet simple enough for non-technical users to set up and manage without extensive training?"
Research & Discovery
I conducted intensive user research over 2 weeks to understand the needs, pain points, and workflows of our target users across different industries, using rapid research methods to maintain velocity.
User Interviews
E-commerce businesses
18 participants
SaaS companies
15 participants
Professional services
12 participants
Research Activities
Contextual inquiry sessions (12 sessions)
Observed users in their work environment
Competitive analysis (8 platforms)
Zapier, Make, Intercom, Drift, Zendesk
Survey distribution (237 responses)
Quantitative data on pain points
Research Insights
82%
Wanted visual workflow builders instead of code-based configuration
91%
Needed unified inbox to manage conversations across all channels
76%
Required real-time analytics to measure agent performance
Key Features & Design Decisions
Each feature was designed with specific user needs in mind, backed by research insights and validated through testing.
Visual Workflow Builder
Drag-and-drop interface for creating complex automation workflows without coding.
82% reduction in setup time
91% user satisfaction score
Design Decisions
Used familiar mental model from tools like Scratch and Notion. Each block represents a single action (trigger, condition, action, response).
Users can test workflows in real-time without saving. Increased confidence by 73% according to post-launch surveys.
AI-powered recommendations for next steps based on industry templates and similar workflows. Reduced decision paralysis by 56%.
Impact Metric
Average time to create first working workflow (vs 23 min with competitors)
Unified Conversation Hub
Single interface to manage all customer interactions across email, chat, SMS, and voice.
68% faster response times
4 tools replaced with 1
Design Decisions
Designed conversation threads that maintain context when customers switch channels. Shows full history regardless of entry point.
Visual badges show how conversation was routed (AI-handled, escalated, manual). Helps teams understand agent performance at a glance.
Human agents can seamlessly take over AI conversations with one click. AI provides context summary and suggested responses.
Impact Metric
100% of customer context maintained across channels (vs 36% before)
Real-Time Analytics Dashboard
Comprehensive insights into agent performance, workflow efficiency, and ROI.
15+ key metrics tracked
Custom report builder
Design Decisions
Designed for quick decision-making: shows hours saved, costs reduced, and customer satisfaction in a glanceable format.
Each workflow has its own analytics page with success rate, execution time, and error tracking for optimization.
AI highlights anomalies and suggests optimizations. "Your checkout workflow is failing 23% more this week. Review error logs?"
Impact Metric
Average cost savings per customer in first 6 months (documented via analytics)
Pre-built Templates
45+ industry-specific workflow templates that users can customize. Reduced time-to-value by 89%.
Most used: Order status, Appointment booking, FAQ handling
Security & Compliance
Designed role-based access control, audit logs, and data encryption. SOC 2 Type II compliant.
Features: SSO, 2FA, data residency controls
Integrations Hub
Connect with 50+ tools via pre-built integrations and custom API connections.
Top integrations: HubSpot, Salesforce, MailChimp, Google
Results & Impact
The platform launched successfully and achieved significant measurable impact across user satisfaction, business metrics, and operational efficiency within 8 months.
82%
Reduction in Manual Workflows
Users automated an average of 67% of previously manual tasks within first month of use
15 hrs
Weekly Time Saved
Average time saved per user per week, translating to 780 hours per year per user
$42K
Average Cost Savings
Average cost savings per customer in first 6 months (labor, tools consolidation)
Business Growth Metrics
1,240+
Active customers
Within 6 months of launch
143%
Of revenue target
Exceeded projections
4.7/5
User satisfaction
Based on 100+ reviews
38%
Month-over-month growth
Sustained growth rate
User Experience Improvements
Task Success Rate
91%
Users successfully complete workflow setup on first try
Feature Adoption
71%
Users adopt 3+ features within first week
Daily Active Usage
67%
Percentage of users who log in daily
Performance Benchmarks
82% faster than competitor average (23 min)
Reduced support burden through intuitive design
Users complete full onboarding process
Key Learnings & Reflections
This project taught me valuable lessons about designing for complex enterprise software, balancing power with simplicity, and the importance of continuous iteration.
What Worked Well
Early and frequent user testing
Testing every 2 weeks allowed us to catch issues early and iterate quickly. This prevented major redesigns later.
Visual metaphors over technical jargon
Using everyday language and visual blocks made AI automation accessible to non-technical users.
Close collaboration with engineering
Daily syncs prevented technical debt and ensured designs were feasible within our timeline.
Data-driven decision making
A/B testing critical features helped us choose the right approach based on evidence, not opinions.
Research Activities
Challenge: Balancing power and simplicity
Solution: Created progressive disclosure—simple by default with advanced options tucked away.
Challenge: Diverse user skill levels
Solution: Built templates for beginners and custom workflow builder for power users.
Challenge: Complex error states
Solution: Designed contextual error messages with suggested fixes instead of generic alerts.
Challenge: Proving value to skeptical users
Solution: Added real-time time-saved calculator and ROI dashboard to show tangible impact.