ZETIC.ai

Brings AI capabilities directly to devices, eliminating cloud server costs and ensuring top performance, energy efficiency, and enhanced data security.
On-Device AI Edge Computing AI Cost Optimization

ZETIC.ai is an on-device AI software that brings cost-effective and efficient AI capabilities directly to devices, eliminating the need for expensive GPU cloud servers. By utilizing NPU-based technology, ZETIC.ai ensures top performance on mobile devices while maximizing energy efficiency.

Ideal for companies concerned about high AI costs, data leaks, and those looking to transition to on-device AI, ZETIC.ai offers several key features. It provides a tailored pipeline for data processing to deployment, including hardware-specific optimization and an on-device AI runtime library. This enables a seamless conversion to on-device AI without loss of core technology.

The automated pipeline streamlines the process, ensuring completion within a day. Additionally, ZETIC.ai enhances data security by processing information directly on devices, reducing the risk of external breaches.

Use cases include model preparation, performance profiling, target library implementation, and on-device application implementation. This comprehensive end-to-end pipeline makes it suitable for various businesses looking to integrate AI technology without incurring significant server costs.

ZETIC.ai offers a free beta version to try, with further pricing options available upon contacting their sales team. By adopting serverless AI, users can significantly reduce costs associated with maintaining GPU servers and cloud services. The platform supports any OS and processor, making it a flexible solution for a wide range of devices.

Users can expect benefits such as strengthened user data privacy, reduced AI service maintenance expenses, and decreased dependency on network environments. For those interested in exploring the capabilities of on-device AI, ZETIC.ai provides a convenient and cost-effective solution.

Published on July 27, 2024

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