In a world where travel can feel exciting for some and unsafe or isolating for others, especially for people from underrepresented backgrounds, personalized and culturally aware trip planning isn’t a luxury it’s a necessity. Yet, most travel platforms today still offer one-size-fits-all recommendations, often overlooking safety, cultural fit, or inclusion.

GreenBookAI was built to change that.

It’s a travel planning tool powered by AI that not only curates personalized itineraries. It does so with an emphasis on trust, safety, and cultural relevance. This post provides a high-level technical look into how GreenBookAI works under the hood, and how we’re using agentic artificial intelligence to build a better travel experience.

If you're curious, I invite you to sign up and test GreenBookAI. It’s still in active development, but the core functionality is already live and your feedback would be incredibly valuable.

Backend Architecture: The Core Intelligence

At the heart of GreenBookAI is a Python-based backend that orchestrates every aspect of the itinerary generation process. This is where most of the intelligence lives.

Multi-Agent System

A standout feature is our use of agentic AI, powered by OpenAI Agents. We’ve created a dedicated Activities Search Agent that performs structured searches and returns detailed JSON responses for businesses.

These results are processed by a central orchestrator that allocates hobbies, restaurants, and content across a multi-day plan based on the user’s travel window and preferences.

Concurrent Processing

To ensure speed, we’ve implemented concurrent async processing using asyncio and httpx.AsyncClient. This allows us to search for multiple types of businesses at once, validate multiple URLs simultaneously, and respond quickly, even when generating multi-day plans

Rate Limiting

To stay compliant with third-party APIs (like OpenAI’s), we use rate limiting via asyncio.Semaphore to throttle concurrent requests and prevent overload.

Frontend Experience: Built in React.js

The user interface is built with React.js & Vite.js, designed to keep things simple but dynamic. The frontend handles:

Collecting user inputs (dates, hobbies, food preferences, etc.)
Sending that data to the backend
Displaying the structured itinerary, complete with location info and image assets from Pexels for added context

It’s a lightweight but functional interface that makes exploring your travel plans feel personal.

Real-World Sharing: What’s Next?

I recently demoed GreenBookAI during a panel at Schneider Electric, where we discussed how AI can be used to make tools more inclusive and context-aware.

The reaction reinforced the need for products like this; tools that don’t just optimize for efficiency, but for empathy and safety too.

There’s still a lot of work ahead but the core engine is live and I’d love for you to give it a try.

Whether you're someone who wants culturally relevant travel suggestions, a builder curious about multi-agent AI systems, or just looking for a fresh take on travel planning. I welcome your thoughts, ideas, and feedback.