🚀 Smart GTM Agent

Turn Weeks of Market Research into Minutes of Execution.

🛑 The Problem

Most Go-To-Market plans fail before launch. Not because teams lack ideas — but because research is slow, scattered, and outdated the moment it’s done. The companies that win aren’t the ones with more data. They’re the ones that decide faster — with clarity.

💡 The Solution

Smart GTM Agent is the AI-powered co-pilot that every founder and growth team secretly wants. It automates the heavy lifting of market research, competitor analysis, and strategy definition, turning them into a structured, actionable playbook in seconds.

No slide decks. No guesswork. Just execution.

🏗️ Architecture & Flow

🌟 Key Capabilities

🔎 Deep Market Research (SmartCrawler)

• Automated Profiling: Instantly extracts team, HQ, socials, and contacts from company URLs.
• Competitor Mapping: Identifies direct and indirect rivals, funding status, and market positioning.
• Industry Landscape: Discovers market opportunities and emerging trends.

📊 Tactical GTM Playbooks

• ICP Definition: Pinpoints your Ideal Customer Profile with demographic and firmographic precision.
• Positioning Strategy: Crafts clear messaging, value propositions, and differentiation angles.
• Pricing & Packaging: Recommends pricing models based on competitive benchmarks.

🌐 Growth & Channel Strategy

• Distribution Channels: Identifies the best mix of direct sales, partnerships, and digital channels.
• Partner Ecosystem: Suggests potential resellers, affiliates, and integration partners.
• Actionable Growth Levers: Provides specific, high-impact tactics for scaling.

⚡ Under the Hood

This project leverages a cutting-edge stack for maximum performance and reliability:

• SmartCrawler: For robust, structured data extraction from any website.
• LangGraph: Determines the control flow and state management of the agentic workflow.
• Nebius Studio: Powered by Hermes-4-70B, an open-source model optimized for complex reasoning and structured output.
• SQLite: A lightweight, serverless database for persistent storage of reports and insights.
• Streamlit: For a beautiful, responsive, and interactive user interface.

🛠️ Installation & Setup

Follow these steps to get your Smart GTM Agent running in minutes.

1️⃣ Prerequisites

Ensure you have the following API keys:

• SmartCrawler API Key: Get it from ScrapeGraphAI.
• Nebius API Key: Get it from Nebius AI Studio.

2️⃣ Clone the Repository

bash
git clone https://github.com/your-username/smart-gtm-agent.git
cd smart-gtm-agent

3️⃣ Set Up Virtual Environment

We recommend using uv for blazing fast package management, but standard pip works too.

Option A: Using uv (Recommended)

bash
# Create venv
uv venv

# Activate venv
source .venv/bin/activate       # Linux/Mac
.venv\Scripts\activate          # Windows

# Install dependencies
uv sync

Option B: Using standard pip

bash
python -m venv venv
source venv/bin/activate        # Linux/Mac
venv\Scripts\activate           # Windows

# Install dependencies (ensure you have a requirements.txt, or install individually)
pip install streamlit langchain langgraph scrapegraph-py langchain-nebius python-dotenv

4️⃣ Configure API Keys

Create a .env file or api.env in the root directory:

bash
# api.env
SMARTCRAWLER_API_KEY=sg_...
NEBIUS_API_KEY=...

Alternatively, you can enter these keys directly in the Streamlit sidebar.

🚀 Usage Guide

1. Launch the App:

   bash
   uv run streamlit run app.py
   

2. Authenticate: Enter your API keys in the sidebar if you haven't set them in .env.
3. Choose Your Mode:
   • Research: For deep-diving into a specific company.
   • Go-to-Market: For generating a full strategy playbook.
   • Channel: For exploring distribution avenues.
4. Input Target: Paste a company URL (e.g., your own or a competitor's).
5. Analyze: Hit the rocket button and watch the agents work their magic! 🪄

📂 Project Structure

text
Day 28 - smart_gtm_agent/
├── app/
│   ├── __init__.py
│   └── agents.py       # Core logic for Research, GTM, and Channel agents
├── assets/
│   ├── banner.png      # Project banner
│   └── nebius.png      # Logo assets
├── company_data.db     # SQLite database (auto-generated)
├── api.env             # Environment variables (excluded from git)
├── app.py              # Main Streamlit application entry point
├── pyproject.toml      # Dependency configuration
└── README.md           # This documentation

🤝 Contributing

Contributions are welcome! Whether it's adding a new agent, improving the prompts, or enhancing the UI.

1. Fork the Project
2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
3. Commit your Changes (git commit -m 'Add some AmazingFeature')
4. Push to the Branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

Built for Day 28 of the 30 Days 30 Agents Challenge

[Generic 30 Days Challenge Link] • [My Twitter/X] • [My LinkedIn]

Made with ❤️ and plenty of ☕