AI-Powered Startup Research Tool for VC Analysts
Evaluate startups in seconds, not hours. DealLens automates the research pipeline so VC analysts can focus on decisions, not data collection.
VC analysts spend 60-70% of their time on manual research — scraping data, reading pitch decks, comparing metrics, and writing investment memos. DealLens eliminates this bottleneck.
- 🔍 Startup Intelligence — Instant company analysis powered by GLM-5.1
- 📊 Automated Scoring — Multi-factor evaluation across market, team, traction, and technology
- 📄 Research Reports — Auto-generated investment memos with key metrics
- ⚡ Real-time Pipeline — FastAPI backend with LangChain orchestration
- 🎨 Clean Dashboard — Next.js frontend with intuitive data visualization
- 🔗 API-First Design — RESTful endpoints for integration with existing workflows
┌─────────────────────────────────────────────────────┐
│ Frontend (Next.js) │
│ TypeScript + Tailwind CSS │
└──────────────────────┬──────────────────────────────┘
│ REST API
▼
┌─────────────────────────────────────────────────────┐
│ FastAPI Backend │
│ ┌─────────────┐ ┌──────────────┐ ┌────────────┐ │
│ │ LangChain │ │ GLM-5.1 │ │ Research │ │
│ │ Orchestr. │──│ Engine │──│ Pipeline │ │
│ └─────────────┘ └──────────────┘ └────────────┘ │
│ ┌─────────────┐ ┌──────────────┐ │
│ │ Scoring │ │ Report │ │
│ │ Engine │──│ Generator │ │
│ └─────────────┘ └──────────────┘ │
└─────────────────────────────────────────────────────┘
- Python 3.10+
- Node.js 18+
- GLM-5.1 API key
# Clone the repository
git clone https://github.com/datawithusman/deal-lens.git
cd deal-lens
# Set up backend
cd backend
python -m venv venv
source venv/bin/activate # Windows: venv\Scripts\activate
pip install -r requirements.txt
# Set up frontend
cd ../frontend
npm installCreate a .env file in the backend directory:
GLM_API_KEY=your_glm_api_key_here
LANGCHAIN_API_KEY=your_langchain_key_here# Start the FastAPI backend
cd backend
uvicorn main:app --reload --port 8000
# Start the Next.js frontend
cd frontend
npm run devimport requests
# Analyze a startup
response = requests.post(
"http://localhost:8000/api/v1/analyze",
json={
"company_name": "TechStartup Inc.",
"website": "https://techstartup.com",
"industry": "SaaS"
}
)
report = response.json()
print(report["score"]) # Overall score: 78/100
print(report["recommendation"]) # "Strong potential — schedule meeting"deal-lens/
├── backend/
│ ├── app/
│ │ ├── api/ # API routes
│ │ ├── core/ # Config & settings
│ │ ├── models/ # Data models
│ │ ├── services/ # Business logic
│ │ └── chains/ # LangChain pipelines
│ ├── requirements.txt
│ └── main.py
├── frontend/
│ ├── src/
│ │ ├── app/ # Next.js app router
│ │ ├── components/ # React components
│ │ └── lib/ # Utilities
│ ├── package.json
│ └── tailwind.config.ts
└── README.md
Muhammad Usman — AI Systems Developer @ Nobel AI
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