AI-native mobile • private by default
On-device AI mobile apps for operations.
Build a working app where AI is inside the workflow — without sending sensitive data to third parties. We optimize for privacy, latency, offline readiness, and measurable quality.
PrivateClear boundaries: what stays on-device vs what leaves the device
FastLow-latency inference where the operator needs it
DefensibleEvaluation plan + telemetry, not “AI theatre”
What we ship
- Cross-platform app (React Native or Flutter) aligned to your constraints
- On-device AI feature(s) embedded in the workflow (not a demo screen)
- Offline-first patterns where needed: queues, sync, conflict strategy
- Instrumentation: latency, success rate, fallbacks, crash reporting
How we de-risk it
- Week 1: workflow map, risk register, prototype, fixed scope
- Weeks 2–4: build + acceptance criteria + pilot readiness
- Evaluation: test sets, failure modes, “stop conditions”
- Governance: explicit data boundaries + audit-friendly hooks
FAQ
Short answers — no slide-ware.
When does on-device AI make sense?
Sensitive data, unreliable connectivity, low-latency needs, or strict cost/governance requirements.
Do you still use cloud AI?
Sometimes. We use a hybrid design when it’s safer or cheaper — with explicit boundaries and redaction.
How do you prove quality?
Evaluation plan + acceptance criteria + telemetry. We measure and iterate, not guess.
How do we start?
Send a workflow description and constraints. We’ll reply with a focused scope and a realistic schedule.