AI-LeadGen-Modular-Agent-Suite

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Introduction

AI LeadGen Modular Agent Suite is a robust, modular platform for automated research and structured lead generation. Built with the Google Agent Development Kit (ADK) and Gemini API, it transforms natural language queries into actionable business intelligence. The system is designed for extensibility, reliability, and real-world impact in recruitment, sales, and market research.

Why Use This Project?

  • Automate complex research tasks: Save hours of manual work by letting AI agents extract, analyze, and generate leads from unstructured queries.
  • Structured, actionable output: Get results in clean JSON and CSV formats, ready for integration or reporting.
  • Modular and extensible: Easily add new agents or tools to expand capabilities for your unique use case.
  • Real-world ready: Designed for business, recruitment, and market intelligence applications.

Key Features

  • Natural language query understanding
  • Multi-agent collaboration (intent extraction, pattern discovery, lead generation)
  • Asynchronous execution for speed
  • Output validation and error handling
  • Easy integration with other systems

System Architecture

The system is composed of three core agents:

  1. Intent Extractor Agent: Converts user queries into structured intent (e.g., location, role, company type, count).
  2. Pattern Discovery Agent: Analyzes data to identify hiring signals, job titles, and relevant business patterns.
  3. Lead Generation Agent: Produces company leads with explanations, target roles, contact suggestions, and confidence scores.

Example Usage

Input:

Find me 10 Sri Lankan IT companies that might hire AI interns in Colombo.

Output:

[
  {
    "company_name": "Sysco Labs Sri Lanka",
    "why_match": "Strong focus on AI and data science...",
    "target_roles": ["AI/ML Intern", "Data Science Intern"],
    "confidence": 95
  },
  ...
]

Results are also saved as a CSV file for easy use.

Quick Start

  1. Clone the repository: 
    git clone <your-repo-url>
cd <repo-folder>
  2. Create and activate a virtual environment: 
    python -m venv .venv
source .venv/bin/activate
  3. Install dependencies: 
    pip install -r requirements.txt
  4. Add your API key: Create a .env file with: 
    GOOGLE_API_KEY=your_api_key_here
  5. Run the system: 
    python main.py

Project Structure

main.py
test_adk.py
requirements.txt
sub_agents/
  intent_extractor/agent.py
  pattern_discovery/agent.py
  lead_generation/agent.py
utils/
  json_rules.py

Extending the System

  • Add new agents in the sub_agents/ directory for additional tasks.
  • Integrate new APIs or data sources as needed.
  • Customize output formats or add new export options.

Contributing

Contributions, suggestions, and bug reports are welcome! Please open an issue or submit a pull request.

Contact

For questions, feedback, or collaboration opportunities, please contact Manav Arya Singh.