The vision pipeline
for complex edge
cases.
IRIN Labs Pvt Ltd provides infrastructure-grade datasets and active inference for rare, safety-critical moments on complex road networks. Built on L4-grade autonomous principles, our pipeline enables predictive safety, even where standard datasets fail. Deploying across NH48 and key urban routes.
Built for the roads
the world missed.
IRIN turns real-world fleet miles into structured, search-indexed edge-case data for ADAS and autonomous systems operating in Indian road conditions.
Dual 1080p HDR streams evaluated on-device.
On-device rare obstacle classification target.
Qwen-VL on low-power Jetson and Raspberry Pi 5 edge nodes.
Structured at the source.
Example event record and sensor envelope for a two-camera vehicle unit.
- CAMERA INPUTS
- 2 × 1080p · HDR · up to 120 FPS
- EDGE BUFFER
- 30s circular RAM · in-memory inference
- EVENT CLIP
- 10s · 5s pre / 5s post trigger
- DETECTOR CLASSES
- Obstacles · vehicles · trajectory · environment
{
"status": "200_OK", "query_execution_ms": 11,
"total_records": 1842,
"results": [{
"clip_id": "clip_nh48_9942",
"timestamp": "2026-10-08T02:14:00Z",
"location": { "lat": 12.9716, "lng": 77.5946, "route": "NH-48" },
"classification": "ANIMAL_INCURSION", "confidence": 0.94,
"s3_video_uri": "s3://irin-data-store/clips/clip_nh48_9942.mp4",
"annotation_uri": "s3://irin-data-store/labels/clip_nh48_9942.json"
}]
}Only the signal
leaves the vehicle.
A privacy-aware edge pipeline cuts routine footage before it reaches the network. Rare events are structured locally, then synchronized when connectivity allows.
Forward and side cameras feed a low-power NVIDIA Jetson or Raspberry Pi 5. A 30-second RAM buffer supplies recent frames to quantized Qwen-VL inference.
Sync on cellular availability READY
Build with the
road ahead.
For fleet operators and autonomy teams building for Indian roads.

