Case Study 2 – GuideFlowAI – From Internal Knowledge Retrieval to Retail AI Assistants

1. The Challenge

Across teams and industries, employees were wasting time searching for internal documentation, policies, and contacts — asking the same questions repeatedly.

With the rise of conversational AI, I saw an opportunity: ask more, search less.

My goal? Build a branded AI assistant that solves internal needs today and can evolve into consumer-facing tools tomorrow.

2. My Role

• Invented and built GuideFlowAI – a GPT-powered internal support chatbot
• Designed a minimalist, conversational UI for clarity and trust
• Created a backend architecture built for future scalability into retail spaces

3. The Solutions

A. GuideFlowAI: Internal Knowledge Retrieval Tool

• Employees ask: “Where do I send invoices?” or “Who handles work orders?”
• AI replies with verified, document-based answers only
• Responses include clickable links to Google Drive files and team contacts
• Branded interface, consistent tone, instant value

Results: More autonomy, fewer bottlenecks, better cross-team communication.

🔗 Live Demo:
Try GuideFlowAI

Note: This is a public mockup. It may take up to 30 seconds to respond after your first question (e.g., “What’s the work order policy?” or “Who manages vendor invoicing?”) as the system initializes.

B. Scalable Retail Vision: AI Personal Shopping Assistant

Using the same AI logic, I created a concept for an intuitive, fashion-forward product chatbot.

Example scenario:
“I’m a curvy woman going to a baby shower. Show me outfit ideas.”

• Tagged catalog data powers curated suggestions
• Outfit combinations, availability, cross-sell logic, and add-to-cart flow
• Conversational, brand-aligned, and deeply personalized

This model scales across industries — fashion, grocery, hardware, or services.

4. Design Thinking in Action

• Conversational tone aligned with brand voice
• UI/UX tested for non-technical users
• Architecture built with scalability in mind
• Repositioned chatbots as brand ambassadors, not utilities
• Used tools familiar to dev teams (Flask, JS, Pinecone, OpenAI, Netlify)

5. Results

• Estimated 40–60% reduction in internal support questions
• Faster onboarding and easier access to knowledge
• Scalable chatbot framework ready for customer-facing use
• Helped reposition AI as a design-forward, creative tool

6. Takeaway

GuideFlowAI proves that a Creative Director can lead product and AI strategy — not just campaigns. When built with intention, chat interfaces become scalable, intuitive extensions of a brand’s voice and value.

This project wasn’t just about deploying GPT. It was about designing an experience that solves real-world problems — from both the inside and out.