device + server • explicit governance

Hybrid AI architecture for mobile apps.

Q: Why hybrid instead of fully on-device?

Some tasks require larger models, shared knowledge, or cross-user context. Hybrid keeps sensitive steps local while using servers where it’s safe and cost-effective.

Q: How do you define boundaries?

We document what data leaves the device, when, and why. We add redaction, consent, and audit-friendly hooks so governance is explicit.

Q: What about outages or latency spikes?

We design fallbacks: on-device degraded mode, cached responses, and workflow steps that continue offline when required.

Not everything should run on-device — and not everything should leave the device. We design explicit boundaries and a pragmatic hybrid plan: privacy, latency, and cost under control.

BoundariesWhat stays local vs what can run server-side

GovernanceRedaction, consent, logging hooks, auditability

ResilienceFallbacks for outages, latency spikes, and offline work

Request a scope checklist Email dp@sternika.com

What we document

Data flow map: what leaves device / tenant
Security controls: redaction, auth, least-privilege
Latency and cost budgets per workflow step
Evaluation plan and acceptance criteria

How we ship

Week 1: workflow map, boundaries, prototype, fixed scope
Weeks 2–4: build + instrumentation + pilot readiness
Fallbacks: degraded modes and offline continuation
Governance: audit-friendly logging hooks and controls

FAQ

Short answers — no slide-ware.

Why hybrid instead of fully on-device?

Some tasks need larger models or shared context; hybrid keeps sensitive steps local.

How do you define boundaries?

We document the data flow and add redaction, consent, and audit hooks.

What about outages or latency spikes?

Fallbacks: on-device degraded mode, caching, and offline continuation where needed.

How do we start?

Share the workflow + constraints. We respond with scope and a realistic schedule.