AWSome Scanner: AI Business Network Analyzer

AWSome Scanner is a serverless web application that transforms physical business cards into organized digital network with actionable insights using AI-powered queries and interactive visualizations.

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🎯 Inspiration

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

So, after exchanging many cards from events like AWS Summits, I decided to digitalize all these cards and allow integration with my phone contact book, and with AI implemented to handle my questions on my network.

💡 The Solution

I built an open-source 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/individually!
  • open-source solution, meaning you can self-deploy and control your data!
  • Providing network analysis and visualization
  • Offering an AI-powered chat interface for querying your contact database

Some quick peek on the product:

View your contacts and save to phone contact Contacts

Gain actionable insights with AI Gain actionable insights with AI

Visualize your professional network Visualize your professional network Visualize your professional network with charts

🚀 Quick Start

Want to try it yourself?

  1. Click this demo url
  2. Sign in using the test credentials:
    • Username: testUser
    • Password: 12345678!
  3. Navigate to the "Scan Cards" tab
  4. Upload one or more business card images
  5. View processed contacts in the "My Contacts" tab
  6. Explore network insights in the "Network Analysis" tab

🏗️ How I built it

Architecture and Data Flow

Let's start with the overall architecture design AWS Architecture Diagram

The application processes business card data through a multi-stage pipeline managed by AWS Lambda that extracts, analyzes, and stores contact information.

The below shows how Lambda handles the pipeline when a new business card image comes in

[Lambda receives card image] -> [Amazon Textract] -> [DeepSeek API] -> [DynamoDB]
           |                    |                   |               |
           v                    v                   v               v
    Image Storage     Text Extraction    Contact Info Parse    Data Storage
    (S3 Backend)                         & Classification

Key Component Interactions:

  1. Frontend (CloudFront + S3) uploads business card images to S3 backend bucket
  2. Lambda function triggers Textract for OCR processing
  3. Extracted text is sent to DeepSeek API for structured data extraction
  4. Parsed contact information is stored in DynamoDB
  5. Frontend retrieves and displays contact data through API Gateway
  6. Network analysis is performed on the stored contacts
  7. Real-time chat interface queries the contact database

Infrastructure components

Networking

  • CloudFrontDistribution (CloudFront): Content Delivery Network (CDN) for caching, reduce latency and better website performance

Storage

  • BackendBucket (S3): Stores business card images
  • FrontendBucket (S3): Hosts the web application
  • MainDynamoDBTable: Stores contact information with userId and cardId as keys

Compute

  • MainFunction (Lambda): Handles API endpoints for scanning, contact management, and network analysis

API & Authentication

  • MainAPIGateway: REST API interface
  • MainUserpool (Cognito): User authentication
  • MainIdentityPool (Cognito): Federated identity management

Security

  • MainIdentityPoolIAMAuthRole: IAM role for authenticated users
  • Bucket policies for secure access to S3 resources
  • AWS Certificate Manager (ACM): Manage SSL/TLS certificates for use with CloudFront CDN

Deployment

  • CloudFormation: deploying infra with IaC approach
  • AWS SAM: ease serverless deployment

😮 Challenges I ran into

There are quite challenges in developing this web app, let me include the most major one here. You cannot scan by camera without HTTPs (or a TLS/SSL certificate)

As I was trying to quickly ship this web app, I didn't know that having this certificate is a REQUIREMENT to enable upload by camera, apparently it would be a security vulnerability without it. Since the ability to upload by camera is crucial to UX, I quickly google the solution. I then figured out that I can use CloudFront to solve this as CloudFront by default has a certificate.

However, the default domain name of CloudFront is hardly user friendly, as the name is too long to remember, so then I proceed to buy a cheap domain elsewhere and handled the DNS config as well.

All is good until I find out that CloudFront could still be bypassed, so I implemented Origin Access Control with S3 as origin, which this took me some time as quite a lot of documentation is still showing the legacy method (using OAI).

So basically it's a chain of problems starting with simple upload by camera issue. But by overcoming this challenge (and other challenges as well), I learned more on the best practices related to web app development.

🔮 Accomplishments that I am proud of

Well this web app is truly a very useful tool that I always use it whenever there are some networking events, and I am also very proud of the fact that all my core features on the wishlist have been accomplished:

  • Upload business card images (single or batch)
  • AI automatically extracts and categorizes information
  • View my contacts in a modern, filterable interface
  • Explore network connections through interactive visualizations
  • Chat with AI to analyze my professional network
  • Easily export contacts as vcard files to my phone contacts

And the fact that now all business cards are digitalized, I can finally gain actionable insights easily with my database.

🤔 What I learned

  1. Serverless architectures need really thoughtful timeout configurations (I had to increaset the integration timeout to 60000ms via service quota request this time...)
  2. User experience is crucial for AI-powered application, I spent more than expected dev time on the frontend part.

What's next for Business Card Scanner: Digitize Professional Network with AI

  1. Better UI/UX and improve latency with AI chatbot.
  2. 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 to decouple this part in the future.

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