Edge Computing
Move processing to where the data is born. Our edge architectures cut latency, reduce cloud bandwidth costs, and keep systems running even when connectivity drops.
Illustrative imageWhat we deliver
Edge Node Design
Selection and deployment of edge compute hardware — from industrial PCs and Raspberry Pi clusters to ruggedized IoT gateways.
Local Inference
Deploy lightweight ML models at the edge for real-time anomaly detection, image classification, and predictive analytics — no cloud round-trip.
Offline-First Architecture
Store-and-forward patterns, local SQLite/InfluxDB storage, and conflict-free synchronization when connectivity resumes.
Edge Orchestration
Kubernetes edge distributions (K3s, MicroK8s) and container orchestration across distributed edge fleets.
Bandwidth Optimization
Intelligent data aggregation, compression, and edge filtering to reduce cloud ingestion costs by up to 80%.
Remote Management
Centralized monitoring, configuration, and OTA updates for edge nodes regardless of network reliability.
Illustrative imageCommon use cases
- Remote industrial sites with poor connectivity
- Real-time safety and anomaly detection
- Video analytics at the edge
- Autonomous vehicles and drones
- Retail in-store AI applications
- Bandwidth-constrained deployments
Related services
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