Edge AI
Models running on-site with no cloud dependency — for latency, connectivity or data that cannot leave the building.
6–12 weeks
When inference has to happen in milliseconds, or connectivity is unreliable, or the data legally cannot leave the premises, the model goes on-site. We optimise and deploy to edge hardware with an update path that does not require someone to visit the plant.
What this solves
- Factory connectivity too unreliable for cloud inference
- Latency budgets cloud round-trips cannot meet
- Data that must not leave the premises
- Bandwidth costs of streaming video to the cloud
What you get
- Model optimisation and quantisation for edge hardware
- On-device deployment and monitoring
- Remote update path
- Offline-first operation with sync when connected
Technology
ONNXTensorRTNVIDIA JetsonDocker
Industries
Talk to the engineers who build it
Tell us the problem and we'll tell you whether edge ai is the right answer — and what it would take.