EasyShip.AI

Table of contents

• Overview
• High Level FLow
  • Architecture Overview
• Key Desing Choices and Trade Offs
  • Key Risks Addressed
• Security and Privacy Posture
• Project Impact
• Project Status
• Screenshot
• Links
• Installation
• Licence
• Authors

Overview

EasyShip reduces manual shipping setup by extracting packing slip data, validating it with a human review step, and returning carrier options with price and service level.A document driven shipping workflow with explicit review before execution.

• Problem: Shipping teams retype packing slip data into carrier tools. Manual entry slows shipment creation and increases pricing and routing errors.

• Who this is for:
Operations or logistics users creating shipments.
Support users reviewing shipment details and costs.

High Level Flow

• The user uploads a packing slip.
Frontend sends the document to an Azure Function.
Azure AI Document Intelligence extracts shipment fields.
User reviews and edits extracted data.
Confirmed data triggers Pitney Bowes Shipping 360 API.
Carrier options return for user selection.

Architecture Overview

• Frontend: React, Tailwind.
• Backend: Azure Function.
• AI service: Microsoft AI Document Intelligence.
• External API: Pitney Bowes Shipping 360.
• Storage: structured shipment records after confirmation.

Key Design Choices and Trade Offs

1. Prebuilt document model over custom training: Faster delivery accepted at cost of lower accuracy on edge layouts.

2. Human review over full automation: Slower flow accepted to prevent costly shipment errors.
3. Serverless function over long running service: Lower ops burden accepted with cold start latency.
4. Single carrier integration over abstraction layer: Faster proof accepted with vendor lock in risk.

Key Risks Addressed


• PII in uploaded documents. Mitigated through minimal retention and no raw document storage.

• Extraction errors. Mitigated through mandatory user confirmation before carrier calls.

• Third party API outage. Mitigated through retries and user facing error states.

• Cost growth from document processing. Mitigated through upload limits and monitoring.

Security and Privacy Posture

• Document uploads treated as sensitive data.

• Processing stays within Azure services.

• Design supports future Entra ID auth, Key Vault secrets, audit logs, and retention timers.

Product Impact

• Reduces manual shipment setup steps.

• Improves pricing accuracy through user validated data.

• Returns carrier options in one screen to speed decision making.

Project Status

• Working proof of concept focused on document intake, validation, and carrier selection.
• If you review this repo as a recruiter
Focus on the DESIGN.md and RISK_REGISTER.md for trade offs, controls, and delivery intent.

Screenshot

Links

• Deployed Application
• GitHub Repo
• EasyShip Presentation Slides

Installation

• To run this project locally, follow these steps:

1. Clone the Repository: git clone https://github.com/yourusername/EasyShip.git cd EasyShip

2. Install Dependencies: npm install

3. Set Up Environment Variables:

• Create a .env file in the root directory and add the necessary environment variables. Example:

  REACT_APP_API_URL=https://api.easyship.com

  REACT_APP_GOOGLE_MAPS_API_KEY=your-api-key

4. Run the Application: npm start

5. Build for Production: npm run build

Licence

This project is licensed under the MIT License. See the LICENSE file for details.

Authors

• GitHub - Andrew Yu | Yuliya Tasheva
• For any questions, suggestions, or issues, please contact our team at

EasyShip.com  ·  Email easyship@gmail.com  ·  Copyright © 2024 All Rights Reserved. Site By Yuliya Tasheva & Andrew Yu®

Thank you for using and contributing to the EasyShip.AI App! Your support helps us continually improve and deliver the best shipping management experience.