Mar 2026 - Present
BeHave
On-device behavior design app running Gemma 3n (INT4) fully offline — 10–30 tok/s on mid-range Android devices, zero cloud dependency.
KotlinJetpack ComposeMVVMLiteRT-LMWork ManagerRoom
An expand on MVVM layering, Room persistence, how behaviors are prompted, WorkManager scheduling.
⚡ Challenges & Solutions
Quantized LLM outputs are noisy and break strict JSON parsers. Built a JSON parser with retry logic and a rule-based fallback path, reaching >95% parse success rate.
📈 Outcomes & Impact
Full local LLM inference on mid-range devices with no API keys, no network calls, no per-token cost — privacy-first by design.