TOMO allows developers to seamlessly deploy, manage, and benchmark local LLMs directly on user devices. Privacy-first, performance-driven.
Shared Intelligence, Zero Redundancy
TOMO follows the same architectural philosophy as push notifications on Android and iOS. Instead of every app bundling its own local LLM/SLM engines and models—wasting storage and potentially overloading device memory—TOMO provides a single, shared resource for all authorized apps.
Traditional Approach (Redundant)
TOMO Philosophy (Shared)
For Developers
Reduced app complexity and smaller binary sizes. Integrate local AI in minutes, not months, using our unified SDK.
For Users
Optimal device performance. No more competing background processes running redundant AI technologies.
Local Deployment
Deploy pre-selected or custom GGUF models directly to user devices for privacy and zero latency.
AI Benchmarking
Automatically benchmarks user devices to determine their readiness for various AI workloads.
Abstraction Layer
A unified LLM provider for all apps on the device, shared through the TOMO app for efficiency.
Developer SDK
Quickly integrate with our robust SDK and use your own custom models for specialized use cases.
Supported Platforms
Develop once, deploy everywhere with TOMO. Native performance across devices.
Android
Full support for Mobile, Tablet, TV, Car (AAOSP), and Android Auto.