Cactus offers a cross-platform inference framework for deploying AI models directly onto mobile devices, enabling low-latency, on-device multimodal processing. This ensures user privacy by keeping data local and optimizes performance through hardware acceleration for edge AI applications.
Funding
Funding not disclosed
Founders
Product
Problem
Deploying AI models on mobile devices often involves significant latency, privacy concerns due to data transmission, and high server costs. This limits the feasibility of real-time, on-device AI applications that require user data to remain local.
Solution
Cactus provides a lightweight, cross-platform inference framework for deploying AI models directly onto mobile devices. It enables on-device, multimodal inference with minimal latency and guaranteed user privacy by processing data locally. The framework leverages hardware acceleration through proprietary kernels to optimize performance for edge AI applications. For more complex tasks, a cloud fallback option is available.
Target Audience
The primary customers are mobile application developers and AI engineers building edge AI solutions for consumer and enterprise mobile platforms.
Features
- On-device, cross-platform AI inference for React Native, Flutter, Kotlin, and C++
- Support for multimodal inference including text, image, and audio processing
- Hardware-accelerated inference utilizing proprietary kernels for optimized performance
- Offline-ready functionality for devices with unreliable or no internet connectivity
- Guaranteed user privacy with all processing occurring on-device by default
- Cloud fallback option for more computationally intensive tasks
- Simple, well-documented APIs for rapid integration
- Low latency with fast Time to First Token and high tokens per second throughput