A new spotlight on Bengaluru’s deep-technology sector is drawing attention to a group of companies building the processors, security systems, communications chips and sensors needed to move artificial intelligence beyond the cloud. The companies reflect a broader transition in India’s technology capital from software outsourcing and application development toward proprietary semiconductor and cybersecurity products with potential customers in the United States.

The July 27 report identified SiMa.ai, Pantherun Technologies, FermionIC Design, Mindgrove Technologies and Steradian Semiconductors as examples of companies working on foundational computing infrastructure. Their products address a central challenge facing the AI industry: advanced models increasingly must operate inside vehicles, robots, cameras, medical equipment and industrial machinery rather than relying entirely on distant data centers.

That shift is creating demand for edge computing, in which data is processed near the device producing it. Local processing can reduce network delays, limit bandwidth use and allow equipment to continue functioning when cloud connections are weak or unavailable. It can also keep sensitive information closer to its source, although distributing computing across thousands of devices introduces additional security and management risks.

SiMa.ai provides the strongest direct connection to Silicon Valley. The company is headquartered in San Jose, California, and describes its platform as a purpose-built system for “physical AI,” a category covering machines that perceive and act in real-world environments. Its machine-learning system-on-chip products are intended to run inference workloads under the power, space and thermal restrictions found in embedded systems.

The company’s target markets include robotics, automotive systems, industrial automation, aerospace and defense, smart vision and healthcare. In September 2025, SiMa.ai and Bengaluru-based L&T Technology Services announced a partnership to develop physical-AI applications for mobility, healthcare, industrial automation and robotics. The arrangement illustrates how a California chip startup can combine Silicon Valley product development with India’s engineering workforce and global enterprise relationships.

For American technology buyers, edge processors are becoming an alternative to using general-purpose graphics processors for every AI workload. Cloud GPUs remain essential for training large models and performing intensive computations, but they can be expensive or impractical inside compact machines. Specialized accelerators instead compete on performance per watt, development simplicity and the ability to support models across different hardware configurations.

Cybersecurity represents the other side of the edge-computing expansion. Every connected robot, camera, vehicle controller or factory sensor can become a new point of exposure. Pantherun Technologies is developing encryption products intended to protect data as it moves among devices, networks and cloud platforms. The company markets hardware and software options for industrial controls, transportation, surveillance, smart-city infrastructure, drones and other connected systems.

Pantherun says its architecture reduces dependence on conventional key exchange by generating encryption information at the communicating endpoints. Its public materials describe products that can be integrated into Ethernet switches, gateways, programmable chips and other networking equipment. The company has also said it intends to expand partnerships and sales in North America, making its development relevant to U.S. operators of industrial and operational-technology networks.

The commercial test will be whether Pantherun’s technology can be independently validated, integrated into existing networks and managed at scale. Cybersecurity buyers generally require extensive testing, standards compliance and clear evidence that a new encryption design does not introduce operational or cryptographic weaknesses. Claims of quantum resistance are receiving particular scrutiny as companies prepare for future computing capabilities while adopting standardized post-quantum algorithms.

Mindgrove Technologies is approaching the edge market from the processor layer. The fabless chip designer is building systems-on-chip based on the open RISC-V instruction-set architecture. Its product materials describe low-power processors for connected devices, security equipment and embedded systems, along with higher-performance designs for computer vision, automotive products and industrial applications.

RISC-V gives designers an alternative to proprietary instruction architectures and allows companies to customize processors for specific workloads. Mindgrove’s Secure IoT product includes hardware security functions, while its developing vision-chip family is intended for cameras, biometric systems, automation equipment and automotive applications. The company says its processors are designed in India, although manufacturing, packaging, software support and customer qualification remain parts of the broader global semiconductor supply chain.

For U.S. companies, the rise of RISC-V designers in India could create both supplier options and competitive pressure. American chipmakers, embedded-device companies and cloud providers are already investing in specialized silicon. New entrants offering lower-power or lower-cost components could win designs in high-volume products, particularly when customers need processors tailored to a narrow set of industrial functions.

FermionIC Design occupies another specialized layer. The Bengaluru fabless company says it develops radio-frequency chipsets for radar, satellite communications and 5G phased-array systems, along with semiconductor intellectual property for system-on-chip designs. Its beamforming products are intended to control signal direction electronically, a capability important to advanced wireless networks, satellite terminals and radar equipment.

Such technologies are less visible to consumers than chatbots or AI applications, but they determine how autonomous and connected machines communicate with their surroundings. They also require long development cycles, specialized engineering teams and close relationships with manufacturers, making them harder to build—and potentially more defensible—than conventional software products.

Steradian Semiconductors shows one route through which Bengaluru-developed technology can enter global markets. The company developed compact, power-efficient imaging radar products before Renesas Electronics completed its acquisition in October 2022. Steradian is now a wholly owned Renesas subsidiary rather than an independent startup, an important distinction when assessing the current landscape.

Renesas said the acquisition would allow it to combine Steradian radar technology with automotive processors, power-management chips, timing products and object-recognition software. The transaction connected a Bengaluru engineering operation with a multinational semiconductor company serving automotive and industrial customers worldwide, including major markets in the United States.

Collectively, these companies suggest that competition over AI infrastructure will extend far beyond the largest cloud platforms. The next stage of deployment will depend on chips that can run models with limited power, networking components that can move data securely and sensors that can operate reliably in difficult physical conditions.

Bengaluru does not yet match Silicon Valley’s concentration of capital, semiconductor companies and global platform businesses. Its deep-tech startups also face familiar obstacles: costly chip development, manufacturing dependence, lengthy customer qualification and the challenge of selling unfamiliar technology to risk-sensitive enterprises.

Even so, the city is becoming a more significant node in the global hardware and cybersecurity market. For Silicon Valley, that creates opportunities for partnerships, acquisitions and access to engineering talent. It also means that more of the intellectual property underlying edge AI may originate outside the United States, as Bengaluru companies move from providing technical services to designing the infrastructure on which intelligent machines depend.