Label, Analyse, and Process Content with One API
The all-in-one content intelligence API for SMBs, developers, and data teams. Automate detection, annotation, classification, and analysis at production scale.
Six Ways to Process Your Content
From single-image inference to batch pipelines — all through one unified API.
Object Detection
Locate and classify objects with precise bounding boxes in real-time. Supports custom & pre-trained YOLO models.
Image Classification
Categorise entire images into your defined classes with Grad-CAM heatmap explanations included.
Segmentation
Pixel-perfect mask generation for defect sizing, measurement, and medical imaging tasks.
AI-Assisted Labeling
Auto-generate bounding box annotations from your images using existing detection models. Reduce labeling time by 80%.
Batch Processing
Submit up to 10 images in a single API call. Ideal for pipeline automation and overnight processing jobs.
Real-time Inference
Low-latency endpoints suitable for live video feeds, edge triggers, and interactive applications.
Built for Teams That Move Fast
Automate quality control and reporting
- Replace manual inspection with AI models
- Integrate into your ERP or MES via REST API
- Custom model hosting on Pro plans
Add computer vision to any app in minutes
- REST API — Python, Node, cURL examples
- Free tier: 300 calls/month, no credit card
- Comprehensive docs with interactive examples
Build training datasets 3× faster
- AI-assisted bounding box annotation
- Export to YOLO, COCO, CSV formats
- Batch API to process thousands of images
From Image to Insight in 3 Steps
No infrastructure to manage. Start processing in under 2 minutes.
Upload or Call the API
Use the web Studio for interactive testing or send images directly to our REST endpoints from your code.
Choose Your Task
Select from detection, classification, segmentation, captioning, or labeling. Mix-and-match in batch calls.
Receive Structured Results
Get JSON with bounding boxes, labels, confidence scores, and optional annotated images instantly.
import requests
response = requests.post(
"https://msightflow.ai/api/detect/",
headers={"Authorization": "Bearer YOUR_API_KEY"},
files={"file": open("image.jpg", "rb")},
data={"model": "yolo_v12_weld", "return_image": "true"}
)
print(response.json())
# → { "objects": [...], "count": 3, "image": "..." }Start Free, Scale When Ready
No credit card required on Free tier. Upgrade as your usage grows.
Ready to Automate Your Content Processing?
Join data teams and developers using mSightFlow to build smarter pipelines.