Solutions & Integration

Get started quickly with our code samples and integration blueprints. Each quickstart guide demonstrates how to connect to the Annie Insights API and make your first successful call.

Available Quickstarts

Language	Use Case	Time to First Call
Python	Data science, backend services, Jupyter notebooks	~3 minutes
C# / .NET	Desktop apps, ASP.NET services, Windows integration	~5 minutes
JavaScript	Node.js backends, serverless functions	~3 minutes

Integration Architecture

All quickstarts follow the same pattern:

1. Set your API key as an environment variable
2. Prepare the request with PatientID, TimeStamp, and ImageName
3. Call the endpoint via HTTP POST (or GET for TLE)
4. Process the response — extract results and download output images

tip

Always make API calls from your backend server, never from client-side code. This protects your API key from exposure.

Common Integration Patterns

Batch Processing

Process multiple images in sequence with rate-limit awareness:

import time

images = ["image1.jpg", "image2.jpg", "image3.jpg"]
results = []

for img in images:
    result = call_api(img)  # Your API call function
    results.append(result)
    time.sleep(6)  # Respect 10 req/min sandbox limit

Webhook-Style Integration

For real-time processing in your clinical workflow:

1. User uploads dental image to your app
2. Your backend sends image URL to Annie Insights API
3. API processes and returns results in ~2-5 seconds
4. Your app displays AI findings to the clinician