Multi-camera intelligence

Efficient enough to run anywhere

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01 // Compression Engine

INT8 Quantization

Detection models are quantized with Kenosis and verified against COCO ground truth. The verification measures detection accuracy itself, not a proxy metric.

02 // Throughput

Lock-Free Pipeline

Every camera runs in its own isolated thread. At real-time tiers the pipeline drops zero frames, and telemetry counter-verifies it.

03 // Reliability

Memory-Safe Core

The pipeline is native Rust and memory-safe by construction, with no Python layer in the serving path.

04 // Routing

Hardware Acceleration

The same build runs on CPU alone, and it picks up CUDA and DirectML acceleration when the host has it.

05 // Observability

Production Telemetry

Prometheus and REST monitoring are built in, with per-stage latency histograms and overload alerting. Every performance claim on this page is reproducible from the daemon's own counters.

Measured — dual-camera headless daemon, re-validated 2026-07-13

30 fps
per camera, two cameras, sustained
22 ms
inference average · 29 ms p95
~120 MB
total working set
2.6 cores
total CPU — 2.6× the core efficiency of FP32

2× 640×480@30 webcams · PP-YOLOE+ S INT8 @320 · Intel i5-13420H · ONNX Runtime CPU · ≥115 s steady-state windows, zero frame drops