India bets big on homegrown AI chips as semiconductor race intensifies

India’s technology ecosystem is entering a decisive new phase, a deeptech renaissance led by semiconductor and AI hardware innovation. A wave of AI chip startups, many founded by former engineers and executives from global giants such as Intel, AMD, NVIDIA, and Texas Instruments, is redefining India’s role in the global semiconductor landscape. These startups are building cutting-edge processors, GaN-based chips, and edge AI accelerators designed to power the next generation of artificial intelligence applications.

Government* *p* *ush : Policy* *m* *eets* *i* *nnovation

The surge in AI hardware entrepreneurship aligns with the Indian government’s long-term vision of technological self-reliance under the Semicon India Programme, a ₹76,000 crore initiative launched to position India as a global hub for semiconductor design and manufacturing.

Within this program, two key components have become the backbone of deeptech growth:

• India Semiconductor Mission (ISM) – tasked with creating infrastructure and policy support for design, fabrication, and talent development.

• Design Linked Incentive (DLI) Scheme – providing financial and infrastructure support to fabless chip startups, reimbursing up to 50% of eligible design costs.

Officials from the Ministry of Electronics and Information Technology (MeitY) have emphasized that design innovation, not just chip manufacturing, will drive India’s strategic autonomy in AI and advanced computing.

Startups* *p* *owering the* *r* *evolution :

Among the rising players are Mindgrove Technologies, InCore Semiconductors, Morphing Machines, Vervesemi Microelectronics, and AiLeap Systems each targeting unique AI hardware segments:

• Mindgrove Technologies (founded by IIT Madras alumni) has unveiled “Secure IoT” chips based on RISC-V architecture optimized for AI edge computing.

• InCore Semiconductors, spun out from IIT Madras’ SHAKTI project, focuses on custom silicon for AI inference and automotive applications.

• Morphing Machines is developing reconfigurable computing architectures that adapt in real time to AI workloads, offering energy-efficient alternatives to GPUs.

• Vervesemi Microelectronics works on GaN (Gallium Nitride)-based power devices, enabling high-performance yet low-power chips crucial for AI data centers.

Many of these ventures are led by veterans who spent decades in global semiconductor companies, now repurposing their expertise to build India-centric solutions that balance cost, efficiency, and accessibility.

Bridging the* *h* *ardware* *b* *ottleneck :

The rise of generative AI models has triggered unprecedented demand for computational power. India’s AI ecosystem from startups to government research labs faces a bottleneck in affordable and accessible AI accelerators.

Indian chip startups are attempting to fill this gap by building custom AI inference chips, neuromorphic processors, and energy-efficient edge devices suited for Indian applications including smart manufacturing, defense analytics, agricultural automation, and telecom networks.

“The opportunity lies not in replicating NVIDIA or AMD, but in creating localized, domain-optimized AI chips,” said a senior executive at one of the leading AI hardware firms.

Global* *c* *ollaborations : Japan, Taiwan, and* *b* *eyond

Recognizing India’s design strength but fabrication limitations, these startups are forming strategic partnerships with global semiconductor ecosystems, particularly Japan, Taiwan, and the U.S.

• India’s recent India–Japan Semiconductor Partnership provides joint access to EDA tools, fab capacity, and R&D exchanges.

• Collaborations with TSMC and UMC foundries enable Indian startups to prototype and scale their designs abroad.

• U.S.-based EDA firms like Synopsys and Cadence have extended training and tool access under the DLI scheme.

These partnerships ensure Indian chip startups can focus on design IP ownership, while leveraging global fabrication and packaging expertise.

Challenges on the* *r* *oad* *a* *head :

Despite rapid progress, India’s AI chip dream faces structural hurdles:

• No commercial fabrication facilities (fabs) are operational yet reliance on overseas foundries increases costs and turnaround times.

• Talent shortages in chip verification, analog design, and physical layout engineering remain acute.

• Venture funding in deeptech is still nascent, as investors traditionally prefer faster-return software startups.

• EDA tool access and licensing costs continue to be barriers for early-stage companies.

Industry experts say it will take at least five to seven years before India sees large-scale chip production unless public-private partnerships accelerate infrastructure development.

Strategic* *i* *mplications : India’s* *t* *ech* *s* *overeignty

The semiconductor movement is not just about innovation, it's about sovereignty. With AI becoming the backbone of defense, digital economy, and strategic industries, control over the chip supply chain is vital.

Analysts see this wave of AI chip startups as a national security imperative as much as a commercial opportunity. From autonomous systems and satellite communication to 5G and 6G infrastructure, domestic chip capabilities are seen as critical assets for India’s future.

Turning* *p* *oint for* *d* *eeptech India* *:

India’s software and IT services revolution put it on the global map in the 1990s. Now, the focus is shifting from code to silicon. With strong policy backing, returning global talent, and growing collaboration with technology leaders like Japan and the U.S., India is quietly laying the foundation for an AI hardware revolution.

If the momentum continues, the next decade could see “Made-in-India AI chips” powering not just domestic innovation, but global computing platforms turning India from a chip consumer into a chip design powerhouse.

India’s AI chip startup wave, led by ex-Intel and AMD engineers and backed by strong government incentives, is transforming the nation into a deeptech hub. Despite challenges in fabrication and funding, strategic partnerships and a focus on indigenous innovation are propelling India toward a new era of AI hardware leadership.