01 / Capabilities
What We Build
On-Device ML
Core ML and TensorFlow Lite for inference that never leaves the device. Zero network dependency.
Privacy-First
Data stays on the user's device. No cloud roundtrips for sensitive predictions.
Hybrid Architecture
On-device for speed and privacy, cloud fallback for complex reasoning. Best of both worlds.
Offline Capable
Full ML functionality without connectivity. Critical for field deployment and remote use cases.
Real-Time Analytics
Sub-100ms inference for live data processing. Sports stats, medical monitoring, industrial IoT.
10-28 Week Delivery
From architecture to App Store. Fixed-scope timelines based on complexity tier.
02 / Process
Development Timeline
Typical 18-22 week delivery for a production AI mobile app.
Discovery
Weeks 1-2Requirements, data audit, architecture decision (on-device vs hybrid)
ML Pipeline
Weeks 3-6Model selection, training, quantization, on-device optimization
App Development
Weeks 7-14UI/UX, native integration, API layer, backend services
Testing & QA
Weeks 15-18Device testing, ML accuracy validation, performance benchmarks
Launch
Weeks 19-22App Store submission, monitoring, analytics, iteration support
Investment Range
$30K – $250K+
Based on complexity, ML model requirements, and deployment targets. We scope every project with a fixed-price architecture review first.
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