S-06.1
On-device inference
Model compression and optimization for embedded and industrial accelerators without unacceptable accuracy loss.
Edge AI Infrastructure
When bandwidth, latency, privacy or uptime rule out the cloud, intelligence has to live at the edge. We select, configure and deploy edge compute that you can run and update with confidence.
Capabilities
S-06.2
GPU-accelerated deployment
Containerized, reproducible deployments with hardware-aware performance tuning.
S-06.3
Industrial edge systems
Hardware selection, thermal and power considerations, and ruggedized enclosures for factory and field.
S-06.4
Distributed AI applications
Applications split across multiple edge nodes and on-premise servers, with orchestration and remote updates.
What you can expect
Engineering commitments
- Data stays on site when it needs to
- Hardware sized to the workload, not over-provisioned
- Fleet updates and monitoring planned from day one
Typical deliverables
- 01Hardware selection & sizing
- 02Optimized model artefacts
- 03Container images & deployment tooling
- 04Fleet monitoring & update strategy
- 05Operations runbook
Engineering consultation
Have a process that needs to see, decide and act?
Tell us about the parts, signals or images you work with. An engineer, not a salesperson, will reply with an initial assessment of feasibility and next steps.