Inspiration

Planning a day out usually means searching across multiple platforms for restaurants, activities, ratings, timings, prices, and directions — and then trying to figure out whether everything actually fits together.

We wanted to make this process simpler.

LocalLens was inspired by a simple idea: instead of making people search for individual places, let them describe the outing they have in mind in natural language.

For example:

"I'm in Ahmedabad. I have ₹4000 for 5 people including 2 kids. I want Sunday lunch plus a kid-friendly activity."

From a request like this, LocalLens can search for relevant local places and build an outing plan around the user's requirements.

What it does

LocalLens is an AI-powered local outing planner that turns natural-language requests into personalized plans using real local listings.

Users can describe:

Their location
Budget
Group size
Food preferences
Activities
Timing
Mood
Special requirements

Instead of returning a generic list of recommendations, LocalLens uses these constraints to create a plan that is relevant to the particular outing.

The goal is to bridge the gap between "I want to go somewhere" and "Here's a practical plan for what you can actually do."

How we built it

LocalLens uses a separate frontend and backend architecture.

Frontend

We built the user interface using React, Vite, JavaScript, and Axios.

The frontend provides a simple natural-language interface where users can describe their outing instead of filling out a long traditional search form.

Backend

The backend is built using Python and FastAPI.

It receives the user's request and coordinates the search and AI processing.

We use:

SerpAPI for local/web search
Gemini API for AI-powered planning
FastAPI for the backend API
REST APIs for communication between the frontend and backend

The overall flow is:

User's outing request
        ↓
React + Vite frontend
        ↓
FastAPI backend
        ↓
Search for relevant local places
        ↓
Process real-world results
        ↓
Gemini
        ↓
Personalized outing plan
        ↓
User