VendorPlus

VendorPlus is an AI-powered supplier follow-up and risk monitoring platform that automates vendor status calls, turns supplier responses into structured delivery intelligence, and highlights vendors that need attention.

VendorPlus replaces repetitive manual supplier follow-ups with an automated workflow:

1. Select vendors that need a status check.
2. Initiate AI phone calls to suppliers through CALL-E.
3. Capture and process the supplier's response.
4. Extract structured delivery information from the conversation.
5. Calculate a vendor risk score based on delivery signals.
6. Escalate high-risk vendors so procurement teams can act early.
7. Track vendors, call history, risk, and escalations from one dashboard.

• Automated vendor calls — initiate supplier follow-ups without manual calling.
• AI response extraction — convert natural-language call responses into structured data.
• Risk scoring — identify vendors that are likely to miss delivery commitments.
• Automatic escalation — surface high-risk vendors for immediate attention.
• Vendor dashboard — monitor vendor status and overall delivery risk.
• Call history — review previous supplier interactions and extracted results.
• Procurement-focused workflow — designed around proactive supplier monitoring rather than reactive follow-up.

• Next.js 14
• React 18
• TypeScript
• Tailwind CSS
• Framer Motion
• Lucide React

• Python
• FastAPI
• SQLAlchemy
• PostgreSQL
• Pydantic
• Uvicorn

• CALL-E for AI-powered phone calls
• Automated conversation result extraction
• Vendor risk evaluation and escalation logic

VendorPlus/
├── backend/
│   ├── app/
│   │   ├── db/             # Database models and schema
│   │   ├── routers/        # API routes
│   │   ├── schemas/        # Request/response schemas
│   │   ├── services/       # Calls, extraction, risk and alerts
│   │   └── main.py         # FastAPI application
│   ├── .env.example
│   ├── Dockerfile
│   ├── entrypoint.sh
│   └── requirements.txt
├── frontend/
│   ├── app/                # Next.js application routes
│   └── package.json
├── docs/
│   ├── apicontract.md
│   └── technical-notes.md
└── README.md

• Frontend: https://vendor-plus-xi.vercel.app
• Backend API: https://vendorplus.fastapicloud.dev
• API Docs (Swagger): https://vendorplus.fastapicloud.dev/docs

git clone https://github.com/Eman2123/VendorPlus.git
cd VendorPlus

cd backend
python -m venv .venv

Windows PowerShell:

.\.venv\Scripts\Activate.ps1

Install dependencies:

pip install -r requirements.txt

Create backend/.env using these variables:

DATABASE_URL=
CALLE_API_KEY=
CALLE_ACCOUNT_EMAIL=
ALERT_EMAIL_FROM=
ALERT_EMAIL_APP_PASSWORD=

This project also requires the CALL-E CLI to place real phone calls:

npm install -g @call-e/cli
calle auth login

This opens a one-time browser login. The resulting session token is cached locally and reused automatically.

Start FastAPI:

uvicorn app.main:app --reload

The API will be available at http://127.0.0.1:8000.

FastAPI interactive documentation:

http://127.0.0.1:8000/docs

Open a second terminal:

cd frontend
npm install
npm run dev

The frontend will be available at http://localhost:3000.

Never commit real credentials or .env files to the repository.

Vendor
  ↓
Scheduled / Manual Status Check
  ↓
CALL-E Phone Call
  ↓
Supplier Response
  ↓
Result Extraction
  ↓
Risk Engine
  ↓
Vendor Risk Status
  ↓
Escalation / Alert
  ↓
Procurement Dashboard

The backend exposes endpoints for vendor management, phone calls, dashboard data, and related procurement workflows.

See docs/apicontract.md for the API contract and docs/technical-notes.md for implementation details.

Supplier delays are often discovered after they have already affected a delivery timeline. VendorPlus focuses on early visibility by checking in with suppliers, interpreting their responses, and turning those conversations into actionable risk signals.

Instead of asking procurement teams to manually chase every vendor, VendorPlus helps them focus on the vendors that need intervention most.

VendorPlus is an active hackathon project and is being developed as a prototype for AI-driven procurement and supplier risk monitoring.

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