Market Lens

Overview

Market Lens is a tool designed to help entrepreneurs and business leaders validate their ideas and identify cost-saving opportunities. It performs competitive analysis and assesses automation potential using AI agents. The system compares user-provided ideas or business decks against existing market players and operations, offering actionable insights.

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How It Works

Validation of Unique Ideas:

1. Input an Idea:
   • Enter your business idea into the search box.
2. Web Search:
   • Market Lens searches for major players in the domain.
3. Market Analysis:
   • Identifies and summarizes competitors' unique market approaches.
4. Comparison:
   • Compares and contrasts the input idea with the gathered market data to determine its uniqueness.
5. Output:
   • Displays relevant companies and a validation result for the idea.

Operational Cost-Saving Suggestions:

1. Input a Founder Deck:
   • Upload a deck containing your company's operational details.
2. AI-Powered Insights:
   • Analyzes the operations and identifies cost-saving measures through automation.
3. Opportunities and Validation:
   • Provides JSON-formatted outputs highlighting specific automation opportunities and their potential cost savings.

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Tech Stack

Backend:

• Language: Python
• Features:
  • Built using FastAPI for quick and scalable API development.
  • Dockerized for streamlined communication between frontend and backend.
• Core Functionality:
  • Handles data analysis, web searches, and automation recommendations using a modular research agent.

Frontend:

• Framework: React + TypeScript + Vite
• Features:
  • Interactive user interface for inputting ideas and founder decks.
  • Displays summarized market analysis and automation opportunities.

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Code Highlights

Prompts:

1. Research Prompt: Guides the AI agent to gather market data and summarize competitor insights.
2. Comparison Prompt: Directs the agent to identify automation opportunities and cost-saving potential, outputting JSON for easy integration.

Key Libraries:

• langgraph: Manages stateful AI operations.
• langchain: Facilitates natural language understanding.
• fastapi: Provides a robust backend framework.
• TavilySearchResults: Conducts web searches to gather information.

Dockerization:

The backend is Dockerized for seamless integration with the frontend and to ensure consistent runtime environments.

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Example API Workflow

1. POST Request to /research:
   • Input:

     {
       "query": "Analyze cost-saving opportunities for our ride-sharing service."
     }

   • Output:

     {
       "result": {
         "opportunities": [
           {
             "name": "Customer Support Automation",
             "description": "Use AI-driven chatbots to handle routine inquiries.",
             "unique_perspective": "Reduces support costs and improves response time."
           }
         ],
         "validation": {
           "automation_validity": "There are significant opportunities for AI automation in customer support, logistics tracking, and fleet optimization."
         }
       }
     }

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Getting Started

Prerequisites:

• Docker installed locally.
• Node.js and npm for frontend development.

Setup:

Backend:

1. Clone the repository and navigate to the backend directory.
2. Build and run the Docker container:

   docker build -t market-lens-backend .
   docker run -p 8000:8000 market-lens-backend