TurinTech, an AI-driven code optimization company, has partnered with Intel to develop a fully offline, on-device version of its AI engineering platform, Artemis, optimized for Intel Core Ultra processors. The platform is designed to run entirely on local devices, providing developers and enterprises with improved performance, security, and cost efficiency without reliance on cloud connectivity.
The offline version of Artemis leverages Intel’s XPU architecture and OpenVINO toolkit, enabling the platform to utilize CPU, GPU, and NPU resources effectively. This allows devices to maintain high performance for AI workloads while freeing system resources for other applications, all while preserving data privacy.
“Through our collaboration with TurinTech, we are making it easier to bring Artemis directly on-device,” said Dennis Luo, Senior Director and GM of AI PC Developer Relations at Intel. “This empowers developers to maximize Intel platform capabilities and provides enterprises with faster, secure, and cost-efficient AI performance.”
TurinTech aims to help organizations optimize code execution, reduce operational costs, and improve sustainability. Intel is also adopting Artemis internally to enhance development efficiency and workload management across engineering programs.
Björn Taubert, Director of Developer Engineering at Intel, noted that the partnership goes beyond technology adoption. “We work closely with TurinTech to ensure Artemis is optimized for Intel hardware, providing improved performance, reliability, and efficiency on local systems,” he said.
Leslie Kanthan, CEO and Co-founder of TurinTech, described the collaboration as a step forward for AI development. “Bringing Artemis on-device with Intel enables faster, more secure, and more sustainable AI development directly on the hardware where it matters,” he said.
As part of the partnership, TurinTech and Intel will showcase Artemis on Intel-powered systems to developers and enterprise partners, demonstrating how AI-powered optimization can enhance performance, efficiency, and reliability across devices and organizations.
