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chore: purge repository of secrets, rename to EXPEDITE, and remove emojis for public release
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README.md

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# Zenith Outbound AI
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# EXPEDITE
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## The Operating System for Autonomous Sales Teams
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Zenith is an intelligent outbound sales platform that automates prospect discovery, enrichment, and personalized email outreach at scale. Using advanced AI agents, job board scraping, and human-in-the-loop approval, Zenith helps sales teams find and contact qualified prospects efficiently.
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EXPEDITE is an intelligent outbound sales platform that automates prospect discovery, enrichment, and personalized email outreach at scale. Using advanced AI agents, job board scraping, and human-in-the-loop approval, EXPEDITE helps sales teams find and contact qualified prospects efficiently.
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## Overview
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Zenith automates the entire prospect outreach workflow:
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EXPEDITE automates the entire prospect outreach workflow:
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1. **Prospect Discovery** - Scrapes 4 job board sources to find companies actively hiring
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2. **Email Enrichment** - Uses Hunter.io to find verified email addresses (60-80% success rate)
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WebSocket (Real-time updates)
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FastAPI Backend (Python 3.12+)
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├─ API Routes
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├─ LangGraph Agent (10 nodes)
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└─ Services Layer
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├─ web_scraper.py (4 job boards)
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├─ email_finder.py (Hunter.io)
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├─ smtp_verifier.py (Email validation)
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├─ neo4j.py (Knowledge graph)
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└─ direct_actions.py (Social media)
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API Routes
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LangGraph Agent (10 nodes)
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Services Layer
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web_scraper.py (4 job boards)
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email_finder.py (Hunter.io)
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smtp_verifier.py (Email validation)
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neo4j.py (Knowledge graph)
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direct_actions.py (Social media)
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Databases
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├─ MongoDB (users, missions, prospects, drafts)
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└─ Neo4j (people, companies, relationships)
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MongoDB (users, missions, prospects, drafts)
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Neo4j (people, companies, relationships)
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External APIs
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├─ Hunter.io (email finding)
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├─ Composio (OAuth + sending)
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├─ Groq (LLM inference)
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└─ LangSmith (tracing)
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Hunter.io (email finding)
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Composio (OAuth + sending)
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Groq (LLM inference)
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LangSmith (tracing)
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```
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**1. Clone Repository**
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```bash
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git clone https://github.com/finalroundai/zenith_static.git
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cd zenith_static
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git clone https://github.com/finalroundai/EXPEDITE_static.git
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cd EXPEDITE_static
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```
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**2. Backend Setup**
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## Project Structure
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```
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zenith_static/
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├── backend/
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├── app/
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├── core/
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├── agent.py # LangGraph workflow
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├── config.py # Settings
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├── sender.py # Email sending
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└── socket.py # WebSocket
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├── services/
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├── web_scraper.py # Job board scraping
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├── email_finder.py # Hunter.io
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├── smtp_verifier.py # Email validation
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└── neo4j.py # Knowledge graph
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├── routers/
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├── missions.py # Mission CRUD
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├── reviews.py # Draft review
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└── scraper.py # Scraper API
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└── models.py # MongoDB models
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├── main.py # FastAPI entry
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├── requirements.txt # Dependencies
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└── .env # Configuration
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├── frontend/
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├── src/
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├── components/ # React components
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├── pages/ # Page components
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├── lib/ # Utilities
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├── App.tsx # Root component
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└── main.tsx # Entry point
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├── package.json # Dependencies
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└── vite.config.ts # Vite config
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└── Documentation/
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├── README.md # This file
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├── TECHNICAL_ARCHITECTURE.md # Complete technical guide
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├── LANGGRAPH_VISUALIZATION.md # Workflow diagrams
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└── PROJECT_STATUS.md # Current status
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EXPEDITE_static/
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backend/
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app/
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core/
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agent.py # LangGraph workflow
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config.py # Settings
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sender.py # Email sending
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socket.py # WebSocket
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services/
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web_scraper.py # Job board scraping
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email_finder.py # Hunter.io
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smtp_verifier.py # Email validation
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neo4j.py # Knowledge graph
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routers/
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missions.py # Mission CRUD
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reviews.py # Draft review
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scraper.py # Scraper API
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models.py # MongoDB models
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main.py # FastAPI entry
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requirements.txt # Dependencies
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.env # Configuration
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frontend/
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src/
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components/ # React components
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pages/ # Page components
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lib/ # Utilities
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App.tsx # Root component
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main.tsx # Entry point
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package.json # Dependencies
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vite.config.ts # Vite config
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Documentation/
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README.md # This file
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TECHNICAL_ARCHITECTURE.md # Complete technical guide
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LANGGRAPH_VISUALIZATION.md # Workflow diagrams
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PROJECT_STATUS.md # Current status
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```
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**Build Backend**
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```bash
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cd backend
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docker build -t zenith-backend .
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docker run -p 8000:8000 zenith-backend
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docker build -t EXPEDITE-backend .
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docker run -p 8000:8000 EXPEDITE-backend
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```
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**Build Frontend**
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```bash
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cd frontend
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docker build -t zenith-frontend .
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docker run -p 5173:5173 zenith-frontend
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docker build -t EXPEDITE-frontend .
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docker run -p 5173:5173 EXPEDITE-frontend
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```
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### Production Deployment
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## Repository
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GitHub: https://github.com/finalroundai/zenith_static
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GitHub: https://github.com/finalroundai/EXPEDITE_static
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Branch: arya (development)
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Main: main (production)

backend/app/agents/scout_agent.py

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# NODE: RESEARCHER
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async def research_node(state: ScoutState) -> Dict:
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"""Execute prospect research pipeline"""
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print("--- 🕵️ RESEARCHER ---")
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print("--- ️ RESEARCHER ---")
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# Extract titles and industries from objective
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obj_lower = state["objective"].lower()

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