The new release includes a real-time multi-camera dashboard, semantic video search, and an upgraded detection pipeline.

Sentinel Core is built around an AI-native architecture:

- YOLOv8 for real-time object detection

- CLIP for semantic search (text-to-video queries)

- FAISS for vector indexing

- FastAPI backend with WebSocket streaming

- Fully air-gapped deployment capable

You can now:

- Stream multiple RTSP/IP camera feeds in a live grid view

- Search footage using natural language (e.g. “blue car near gate between 2-5pm”)

- Perform cross-camera semantic retrieval

- Configure zone-based alerts

- Run everything locally without cloud dependency

We designed this as a foundational engine for modern surveillance and physical AI systems.

Would appreciate feedback on:

- Architecture decisions

- Performance optimizations

- Semantic search accuracy

- Deployment improvements

Happy to answer technical questions.