Edge AI Deployments
AI models that run on devices, not the cloud, for low latency and privacy. We compress models and ship them with ONNX, TensorRT, Core ML, and llama.cpp.
Service overview
Reply within 1 business day
Our process for edge ai deployments
A fixed four-step path from first call to production — with weekly demos and a hard launch date.
Discovery & data audit
We map your use case, evaluate data readiness, and define success metrics and guardrails up front.
Deliverable
Feasibility report & eval plan
Model & pipeline design
We architect the retrieval, model, and orchestration layers with cost, latency, and safety in mind.
Deliverable
Architecture & prompt/eval harness
Build, evaluate & harden
We build with a regression eval suite, add guardrails against prompt injection and PII leaks, and tune quality.
Deliverable
Tested system & eval dashboard
Deploy & monitor
We ship to production with telemetry, cost controls, and one-click rollback, then hand over full ownership.
Deliverable
Live system, docs & handover
See where your project fits.
Book your systems auditAI where the data lives
Some tasks can't wait for a cloud round-trip. We deploy AI models directly to devices, factories, and local sites where latency, privacy, or bandwidth are critical.
- Model compression: We optimize models for specific hardware—GPUs, NPUs, and CPUs—using techniques like quantization and pruning.
- Runtime engineering: We use ONNX, TensorRT, Core ML, and llama.cpp to ensure models run within strict memory and power limits.
- Fleet management: We handle remote updates, device health monitoring, and rollback across large groups of devices.
- Hybrid systems: We build setups that run locally but can use the cloud as a fallback or for data processing.
Performance targets
Edge AI starts with a hardware budget. We design for your specific devices and measure every watt and millisecond.
- Latency: We aim for single-digit millisecond response times on standard edge hardware.
- Efficiency: We size models to fit your device's memory while maintaining high accuracy.
- Reliability: All deployments include full monitoring and verified updates from day one.
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Learn moreReady to build edge ai deployments?
Every project starts with a clear scope and a fixed timeline. Tell us what you're building and we'll reply within one business day.