Mythic AI Enters India, Eyes Data Centre and Robotics Growth

Mythic AI enters India with a Bengaluru Centre of Excellence, planning to expand its team and target data centres, robotics, automotive and edge AI through energy-efficient analogue compute-in-memory technology.

US-based semiconductor startup Mythic AI has entered India with a new Centre of Excellence (CoE) in Bengaluru as it looks to expand its presence in the country and tap opportunities in data centres, robotics, automotive and other AI-intensive applications. The company plans to develop the Bengaluru facility into a key engineering and business hub for its operations in Asia.

Founded in 2012 and headquartered in Austin and Palo Alto, Mythic AI develops analogue compute-in-memory technology designed to improve the energy efficiency of AI inference. Its architecture performs computation within memory, reducing the need to move data repeatedly between memory and processors.

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The company currently has close to 20 employees in India and plans to increase the local team to more than 60 by the end of the first quarter of 2027, according to Chairman and CEO Taner Ozcelik. The Bengaluru centre is expected to build specialised capabilities across chip design, physical design, design-for-test, systems engineering and applications engineering.

The CoE will initially contribute to Mythic’s Vanguard platform. Over time, the company plans to expand its India operations into product engineering, test and characterisation, systems engineering and intelligent sensing chip development. Ozcelik said the company intends to develop capabilities that could allow certain products to be designed and taken to market entirely from India.

Mythic is also evaluating opportunities across India’s growing AI infrastructure and industrial technology ecosystem. The company is targeting data centres, automotive and robotics, where demand for energy-efficient AI inference is increasing. Its technology is also designed for applications including advanced driver-assistance systems, enterprise AI, defence and edge computing.

For data centres, the company sees its low-power AI architecture as relevant to inference workloads that require significant computing capacity and energy. In robotics and automotive applications, energy efficiency and local processing can be important for systems that need to analyse data close to where it is generated.

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Ozcelik, who previously served as vice president and general manager of Nvidia’s automotive division, said India offers a strong semiconductor engineering talent pool and education ecosystem. The company intends to use this base to strengthen its chip development capabilities and support its longer-term product roadmap.

The India expansion comes as the country develops capabilities across semiconductor design, advanced packaging, electronics manufacturing and AI infrastructure, providing international chip companies with opportunities to establish engineering and R&D operations.