Technology
Production-grade edge inference stack
Our on-device inference stack optimizes practical performance: latency, memory footprint, energy, and reliability.
Model Optimization
- Quantization (int8/int4), mixed precision
- Pruning and distillation for edge budgets
- Operator fusion and graph optimization
Runtime and Acceleration
- Device-specific kernels and scheduling
- CPU, GPU, and NPU backend strategy
- Stable streaming for multimodal IO
Evaluation and Shipping
- Latency, memory, and battery profiling
- Quality and alignment checks for multimodal outputs
- Release pipeline: artifacts, versioning, and rollback