This is a proof-of-concept for an AI-powered LinkedIn automation platform designed for B2B sales professionals, recruiters, and founders. It moves beyond simple automation by using Context Engineering to understand user goals, analyze profiles deeply, and generate tailored messages that resonate.
The core of this project is a system that:
- Understands user goals and ideal prospect criteria.
- Extracts insights from LinkedIn profiles using NLP.
- Generates tailored connection and follow-up messages.
- Automates outreach sequences without losing personalization.
The platform uses a detailed form to give the AI context to find, filter, and message the right people. The form includes fields for:
- Product/Service: What you're offering.
- Target Industry: SaaS, EdTech, Finance, etc.
- Ideal Job Roles: CTO, Head of HR, Growth Manager, etc.
- Company Size: Startup, SME, Enterprise.
- Region/Location: India, US, Global, etc.
- Outreach Goal: Book a call, demo, hire, network.
- Brand Voice: Formal, friendly, enthusiastic.
- Optional Triggers: Job change, hiring post, new funding, etc.
- Profile Analyzer: Reads LinkedIn bios, work history, posts, and interests.
- Personalized Messaging: GPT-powered connection and follow-up messages.
- Outreach Sequencing: Simulates human-like delays in DMs.
- Smart Prospecting: Filters leads based on ICP and contextual triggers.
- Response Dashboard: Track connection rates, replies, and campaign ROI.
- Frontend: React.js
- Backend: FastAPI
- AI & NLP: OpenAI GPT, spaCy/NLTK for profile analysis
- Database: MongoDB
- Node.js
- Python 3.8+
- MongoDB
- Clone the repo
git clone [https://github.com/your_username_/Project-Name.git](https://github.com/your_username_/Project-Name.git)
- Install NPM packages
npm install
- Install Python packages
pip install -r requirements.txt
- Enter your API keys in
.env
- Start the backend server
uvicorn server:app --reload
- Start the frontend server
npm start