Pocket Mind
Open-source mobile client built to execute AI models locally on-device without internet access. Includes full BYOAPI settings for custom endpoints, RAG parameters, and personas.
1. Project Overview & local AI Context
Pocket Mind was built to resolve mobile data privacy constraints. Developers and consumers want access to offline generative assistants without exposing sensitive query structures to cloud APIs. The challenge was compiling lightweight quantized models (such as LLaMA or Gemma) to execute locally within the mobile hardware footprint, and providing a clean Bring Your Own API (BYOAPI) dashboard for custom API routing.
2. Mobile & AI Engineering Details
CYPHEX engineered a custom offline-compatible React Native app:
- Local Inference Engine: Configured local runtime hooks utilizing mobile-optimized execution libraries, loading lightweight model structures in under 3 seconds.
- BYOAPI Custom Portals: Designed a developer settings panel to input custom endpoints and bearer tokens. This enables testing fine-tuned models directly inside the chat screen.
- Vector RAG Embeddings: Integrated a local SQLite vector database to chunk and load files locally, enabling secure offline Retrieval-Augmented Generation.
- Dynamic Custom Personas: Built structured JSON templates to load and test various chat system instructions on-the-fly.
3. Pocket Mind Developer Dashboard
Performance Standards
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