Business Card Solution powered with DeepSeek

Building a Modern Business Card Scanner with AI: A Deep Dive into AWS and DeepSeek Integration

Hey there, fellow developers! 👋 Today, I'm excited to share my journey of building a modern business card scanner application that leverages AI to transform physical business cards into organized digital contacts. This project combines AWS services with the DeepSeek API to create a powerful networking tool.

🎯 The Problem

In today's digital age, we still exchange physical business cards, but managing them efficiently is a challenge:

• Cards get lost or damaged
• Manual data entry is time-consuming and error-prone
• It's hard to analyze your professional network effectively
• Finding specific contacts or seeing connections between companies is difficult

There are existing digital business card scanning solution in the market, but they are often:

• expensive
• not user friendly
• only supports internal address book, no integration with device contacts
• data stored in the providers' database, you don't own the data

💡 The Solution

I built a web application that solves these problems by:

• Using AI to extract information from business card images
• Organizing contacts with rich metadata
• Allows importing the contacts to your phone contacts in batch!
• self-deployable solution, meaning you own and control your data!
• Providing network analysis and visualization
• Offering an AI-powered chat interface for querying your contact database

🏗️ Technical Architecture

The application is built on a modern serverless stack:

Key Components:

1. Frontend:

   • Single-page application hosted on S3
   • Interactive network visualization using D3.js
   • Real-time chat interface
   • Responsive design with Tailwind CSS

2. Backend:

   • AWS Lambda for serverless compute
   • Amazon Textract for OCR
   • DeepSeek API for intelligent data extraction
   • DynamoDB for contact storage
   • S3 for image storage

3. Authentication:

   • AWS Cognito for user management
   • Secure API access with IAM roles

🔍 Key Features

1. Intelligent Card Scanning

def parse_with_deepseek(raw_text):
    prompt = (
        "Extract the following information from the provided business card text: "
        "name, company, department, title, email, phone, address, website. "
        "Additionally, categorize the company's industry..."
    )
    # DeepSeek API integration for smart data extraction

2. Network Analysis

function updateNetworkVisualization() {
    // D3.js force-directed graph
    const simulation = d3.forceSimulation(nodes)
        .force("link", d3.forceLink(links).id(d => d.id))
        .force("charge", d3.forceManyBody())
        .force("center", d3.forceCenter(width / 2, height / 2));

3. AI-Powered Chat Interface

def handle_chat_message(event, cors_headers):
    """Handle chat messages using DeepSeek."""
    # Process natural language queries about your contacts
    # Generate insights and recommendations

🚀 Getting Started

Want to try it yourself? Here's how:

1. Clone the repository:

git clone <repository-url>
cd business-card-scanner

1. Install dependencies:

cd application
pip install -r requirements.txt

1. Configure AWS and DeepSeek:

Environment:
  Variables:
    DEEPSEEK_API_KEY: 'YOUR_API_KEY'

1. Deploy:

./deploy.sh

🎨 User Experience

The application provides a seamless experience:

1. Upload business card images (single or batch)
2. AI automatically extracts and categorizes information
3. View your contacts in a modern, filterable interface
4. Explore network connections through interactive visualizations
5. Chat with AI to analyze your professional network
6. Easily export contacts as vcard files for your phone contacts

💰 Cost Estimation

AWS: Total 12 months cost = 15.00 USD AWS Pricing Calculator

DeepSeek API: minimum spend = 10RMB = 1.38 USD (1USD = 7.24 RMB)

Total Annual Cost = AWS+DeepSeek key = 15+1.38=16.38= around 16.5 USD

main assumptions:

Number of API Requests 1000 API requests each day x 20 working days = 20000 API requests per month
Number of scan card requests: 1 card each day x 30 days = 30 requests

🔮 Future Enhancements

I'm planning to add:

1. Maybe with https so that the can directly scan with device mobile
2. Better UI/UX and improve latency with AI chatbot.
3. The current serverless architecture is a "Lambdalith", which is great for quick development for PoC but does not scale well with more features coming in. So may need decouple this part in the future.

🤔 Key Learnings

Building this project taught me several valuable lessons:

1. Serverless architectures need thoughtful timeout configurations
2. User experience is crucial for AI-powered application

🎁 Open Source

This project is open source! Feel free to:

• Star the repository
• Submit issues or feature requests
• Contribute improvements
• Fork and adapt for your needs

🔗 Resources

• GitHub Repository
• Live Demo

👋 Connect

I'd love to hear your thoughts and suggestions! Connect with me:

• GitHub: [https://github.com/john-ng-hk]
• LinkedIn: [https://www.linkedin.com/in/john-nch-hk/]

Let me know in the comments if you'd like to see more detailed posts about specific aspects of this project!