CASE STUDY
Buddy AI — Your Intelligent Journey Co-Pilot
For Global Pathways Inc.
We developed "Buddy AI," a next-generation web platform that acts as the ultimate co-pilot for international journeys, leveraging a powerful AI personalization engine to simplify planning for study, work, and travel.
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Client
International Education Consultancy
Industry
EdTech / Travel Tech / AI
Duration
6 Months
Services
Technologies Used
Project Overview
We developed "Buddy AI," a next-generation web platform that acts as the ultimate co-pilot for international journeys, leveraging a powerful AI personalization engine to simplify planning for study, work, and travel.
Development Timeline
Our structured approach to delivering this complex project
Phase 1: Architecture & Data Modeling
Designed the graph database schema and microservices architecture for personalization.
Phase 1: Architecture & Data Modeling
Designed the graph database schema and microservices architecture for personalization.
Phase 2: Core Platform & AI Development
Built the Next.js frontend, core APIs, and the conversational AI engine.
Phase 2: Core Platform & AI Development
Built the Next.js frontend, core APIs, and the conversational AI engine.
Phase 3: Content & Feature Expansion
Integrated the university and travel data, built the comparison tools, and conducted user testing.
Phase 3: Content & Feature Expansion
Integrated the university and travel data, built the comparison tools, and conducted user testing.
System Architecture
A high-performance, decoupled architecture built for complex data relationships and AI-driven personalization at scale, ensuring a responsive user experience.
Technical Stack Overview
Frontend
A highly interactive and animated web app built with Next.js and Framer Motion.
API Gateway
A GraphQL gateway providing a unified data graph for the frontend to efficiently query multiple backend services.
Backend Microservices
A suite of Python (FastAPI) and Node.js services for handling specific domains like user profiles, recommendations, and content.
Data & AI Layer
A Neo4j graph database for the recommendation engine, PostgreSQL for transactional data, and Genkit for conversational AI flows.
Architecture Diagram
The Challenge: Navigating the Overwhelming Maze of International Planning
Planning a major international journey is a process filled with anxiety, information overload, and decision paralysis. Users are left to piece together information from countless disconnected sources.
Users drowning in generic information that isn't relevant to their unique profile.
Difficulty in comparing complex options, like university programs with nuanced admission criteria.
Lack of a single, trusted platform to guide them from discovery to decision.
High user drop-off due to a frustrating and non-personalized experience.
Our Solution: A Hyper-Personalized, Conversational Journey Advisor
1Discovery & Strategy
We identified that the core problem was not a lack of information, but a lack of *guidance*. Our solution was to build an AI that could understand user intent and provide tailored pathways, not just search results.
2Development & Implementation
We architected a sophisticated backend using Python, FastAPI, and a Neo4j graph database to map the complex relationships between destinations, universities, and user profiles. This powers a hyper-personalization engine that communicates with the user through a Genkit-powered conversational AI on a sleek Next.js frontend. A GraphQL API acts as an efficient data layer between the frontend and the various backend microservices.
3Key Features & Capabilities
Conversational AI for natural language-based journey discovery.
Hyper-personalization engine that recommends best-fit universities and travel plans.
Dynamic university comparator to evaluate complex criteria side-by-side.
Unified dashboard to save, track, and manage all aspects of a journey.
Graph database (Neo4j) to power complex, relationship-based recommendations.
Project Showcase
Explore the visual journey of our development process and the final product
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Transforming Information Overload into a Guided Conversation
The numbers speak for themselves. Here's the measurable impact we delivered for our client.
75%
Reduction in user research time
Users found relevant information in minutes through the AI chat, compared to hours of manual searching.
50%
Increase in user conversion
Personalized pathways and clear comparisons led to a higher rate of users taking the next step (e.g., saving a university application plan).
94%
User satisfaction with recommendations
The personalization engine, powered by the graph database, provided highly relevant and useful suggestions.
These results demonstrate our commitment to delivering measurable business value through innovative technology solutions.
Client Testimonial
Hear directly from our client about their experience and the impact of our solution
"Buddy AI is the future of personal planning. InBenne Technologies built an incredibly intelligent platform that truly understands user intent. Their expertise in both AI and complex backend architecture was evident throughout the project."
Dr. Sarah Williams
Director of International Programs, Global Pathways Inc.
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