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Venture Scope

Venture Scope is a comprehensive business intelligence platform designed to help entrepreneurs and businesses make data-driven decisions about market opportunities, location intelligence, and competitor analysis. The platform integrates advanced analytics, machine learning, and natural language processing to provide actionable insights.

Project Overview

To create a comprehensive startup advisory system, the project integrates data from Free Company Dataset (Snowflake) combining with yfinance to fetch financial side of data for available companies. Along with MCP-integration of google maps to figure out the rich details on the ideal or potential locations for the user. These reports are supported by Q&A agents along with VC investment quarterly reports to address and serve as a platform that will provide users with a base for questing and analyzing his interest in specified business domains, company size parameters, and location preferences to generate tailored recommendations and insights.

Deployed Links

Architecture Diagram

architecture_diagram

Features

  • Market Analysis: Gain insights into market trends, consumer behavior, and growth opportunities.
  • Location Intelligence: Identify optimal business locations based on demographics, competition, and other factors.
  • Competitor Analysis: Understand competitors' strengths and weaknesses to develop effective strategies.
  • Q&A Chatbot: Ask questions about your business analysis and get personalized answers.
  • Expert Chat: Interact with virtual representations of industry experts for advice and insights.

Getting Started

Prerequisites

  • Python 3.10+
  • Docker
  • Node.js (for MCP server if required)
  • AWS credentials for S3 integration
  • OpenAI API key for embeddings and chat models

Installation

  1. Clone the repository:
git clone https://github.com/your-repo/venture-scope.git
cd venture-scope

Set up the environment variables:

  1. Install dependencies:
pip install -r requirements.txt
  1. Set up the Airflow environment:
cd airflow
docker-compose up
  1. Run the frontend:
cd frontend
streamlit run app.py
  1. Start the backend:
cd backend
uvicorn app.main:app --reload

Usage

Open the Streamlit frontend at http://localhost:8501. Configure your business details in the sidebar. Generate insights, analyze locations, and interact with the Q&A chatbot or expert chat.

API Endpoints

The backend provides several endpoints for analysis:

/market_analysis: Analyze market trends and competitors.
/location_intelligence: Get location-specific insights.
/q_and_a: Ask questions and get answers based on generated reports.
/chat_with_experts: Generate a comprehensive business summary.

Technologies Used

  • Frontend: Streamlit, Plotly
  • Backend: FastAPI, Pydantic
  • Data Pipelines: Apache Airflow
  • AI Models: OpenAI GPT, Pinecone for vector search
  • Storage: AWS S3
  • Database: Snowflake

Acknowledgments

OpenAI for GPT models Pinecone for vector search Streamlit for the interactive UI Apache Airflow for workflow orchestration