Solutions
Edge AI
Not every AI workload can depend on a round trip to the cloud — latency, bandwidth, privacy, and connectivity constraints often say otherwise.
We design and deploy edge AI architectures for local, low-latency inference that keeps working when the network doesn't.
What it is
Edge AI runs inference on or near the device generating the data — a factory floor gateway, a vehicle, a local server — rather than sending every request to a centralized cloud service.
It exists to address constraints that cloud-only architectures struggle with: latency-sensitive decisions, limited or intermittent bandwidth, data privacy requirements, and the need to keep operating during network outages.
Where it helps
Edge AI is the right fit for use cases with hard latency requirements (real-time inspection or control), remote or bandwidth-constrained sites, environments with strict data-locality requirements, and operations that must continue functioning during connectivity loss.
What PacificTahoe does
We assess hardware constraints (compute, memory, power) at the deployment site and select or optimize models accordingly, including techniques such as quantization and distillation where appropriate.
We design the full operational lifecycle, not just the initial deployment: how models are updated in the field, how performance is observed remotely, and what the system does when it can't reach central infrastructure — a defined fallback behavior rather than an unplanned failure mode.
- Hardware assessment and model selection/optimization for edge constraints
- Deployment and fleet management for distributed edge devices
- Remote observability and performance monitoring
- Update management and defined offline/degraded-mode behavior
Integration considerations
- Available compute, memory, and power at the edge location
- Connectivity patterns: always-on, intermittent, or air-gapped
- How edge devices synchronize with central systems when connected
Governance & security considerations
- Data handling and retention policy for data processed locally
- Security hardening for physically accessible or remote devices
- Version control and rollback for models deployed in the field
Working with latency, bandwidth, or connectivity limits?
Let's assess whether edge AI fits your environment.