To create a user-friendly gateway to a suite of sophisticated AI tools designed for the Web3 ecosystem. This involved not only developing the interface but also defining the visual language and user experience to make complex functionalities intuitive and accessible to both novice and expert users. The challenge was to design a platform that felt both cutting-edge and approachable.

• Lack of technical skills.
• Poor integration with knowledge sources.
• Limited customizability to match brand identity.

We aimed to design GenAi, a no-code chatbot builder that allows anyone to create and deploy powerful AI chatbots using their own data—without writing a single line of code.

• Enable non-technical users to build intelligent chatbots.
• Provide seamless knowledge base training and customization.
• Offer multilingual support and analytics to track performance.
• Design for scale—from startups to large enterprises.

User Research

We conducted:

• 8 stakeholder interviews (Support agents, SMB owners, SaaS founders).
• 3 surveys with 150+ potential users from startups and customer service teams.

Key Insights:

• Users want an intuitive interface—no technical jargon.
• Many want to train bots with existing docs, websites, FAQs.
• Branding control (colors, icons) is essential for trust.
• Real-time analytics and multilingual support were major plus points.

Personas

• Persona 1: Sarah – Support Lead at a SaaS Startup
  • Wants to automate 50% of queries.
  • Needs easy integration with help docs.
• Persona 2: Raj – Solo Founder
  • Has no technical background.
  • Needs a simple, guided builder to launch chatbot fast.

We ran 2 design sprints and mapped the following key flows:

• Chatbot Creation Wizard (Step-by-step setup)
• Visual Flow Builder (Drag-and-drop logic)
• Knowledge Base Upload
• Widget Customizer
• Analytics Dashboard

Wireframes: Created mid-fidelity in Figma, iterated based on feedback from early testers and stakeholders.

We designed a clean, minimal interface with:

• Soft colors and rounded edges to reduce cognitive load.
• Modular cards for drag-and-drop interactions.
• Clear CTAs like “Train with Website” or “Add Logic Block.”

Accessibility: Followed WCAG 2.1 AA guidelines.

Branding: Allow users to set widget colors, bot name, icons to match brand.

3 rounds of testing with 12 users each (remote via Maze & Zoom).

Before Iteration:

• 40% dropped off during “knowledge base” setup.
• Confused about what data the bot was learning.

After Iteration:

• Added inline tooltips & content previews.
• Completion rate improved to 92%.

• Visual Flow Builder: Drag-and-drop system to define how bots respond.
• Knowledge Base Integration: Upload PDFs, links, FAQs. Bot trains instantly using AI (GPT-4 & Claude models).
• Chatbot Widget Customizer: Adjust colors, icons, bot persona, and tone of voice.
• Analytics: View user questions, top drop-offs, engagement rate, resolution time.
• Multilingual Support: 85+ languages with smart language detection.

• 85% of users created their first bot in under 15 minutes.
• 60% reduction in support queries for pilot clients.
• 4.7/5 average CSAT for chatbot performance.
• 73% adoption rate among early users in the first 2 weeks.

• Integrate voice support.
• Launch mobile version.
• Add conversational A/B testing features.

• Simplicity is power: Users preferred fewer features that “just worked” over complexity.
• Visual feedback builds confidence: Real-time previews made the system feel “alive” and helpful.
• Inclusive design drives adoption: Multilingual support was a game-changer for global teams.

Final Thoughts: GenAi is more than just a chatbot builder—it's a productivity and customer engagement tool that gives power back to business owners and support teams. This project exemplified the impact of a truly user-centered design approach, where every decision was driven by empathy, feedback, and iterative validation.