Edge Computing
Deciding what runs at the edge and what runs centrally, then making the split survivable — offline behaviour, sync, versioning and observability.
Delivered on edge runtimes and gateway hardware from third parties. Edge AI work is early and labelled as development, not as a product.
Definition, without the vocabulary game.
Edge computing places computation near where data is produced, instead of sending everything to a central cloud.
Our actual scope of work.
Deciding the split between edge and centre, then making it survivable: offline behaviour, sync and conflict handling, versioned deployment with rollback, and observability across sites.
Where it is used.
- Low-latency inspection and control loops
- Sites with unreliable connectivity
- Bandwidth reduction on video and telemetry
- Data-sovereignty-constrained processing
How a system in this area is layered.
Current status
In development on third-party edge runtimes and gateway hardware. Edge AI work is early.
Future direction
Reference edge AI deployment patterns for manufacturing and infrastructure monitoring.
What this division covers.
- Edge Architecture
- Edge AI Inference
- Offline-First Behaviour
- Sync & Conflict Handling
- Edge Deployment & Rollback
- Latency-Sensitive Workloads
- Data Sovereignty at Edge
- Edge Observability
Discuss a edge computing engagement.
Founder-led scoping, written architecture, no sales layer.