Insights
India’s semiconductor opportunity is moving beyond manufacturing
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Watch the CNBC-TV18 conversation with UST COO Gilroy Mathew and Kaynes Technology CEO Raghu Panicker
India’s semiconductor debate is often framed around fabs, incentives, and manufacturing capacity. Gilroy Mathew sees a broader opportunity taking shape: connecting the engineering that defines a product with the manufacturing capability required to build it at scale.
One team can design a product, another can validate it, a third can assemble it, and yet another can manufacture it. Each handoff creates another place for requirements to drift, decisions to slow down, and responsibility to become less clear. As electronics become more intelligent, those gaps become increasingly expensive.
In the CNBC-TV18 discussion The Smart Manufacturing Shift, Mathew describes the direction as an end-to-end engineering-to-manufacturing model. His perspective reflects 17 years of semiconductor work spanning embedded systems, VLSI, verification and validation, hardware-software integration, and automation. The bigger point isn't the breadth of any one company’s portfolio. It is that customers increasingly want fewer boundaries between those disciplines.
“Nobody really wants five different partners coming in and doing components in five different ways. The overall risk is too high.” — Gilroy Mathew
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“Design and build in India” changes where value is created
India already has a substantial semiconductor design base. The next step is to connect more of that capability with testing, packaging, assembly, electronics manufacturing, and product industrialization. That shift is more consequential than increasing domestic production alone.
Manufacturing something in India does not automatically mean the engineering knowledge, product decisions, and commercial value remain in the country. The opportunity grows when more of the journey can be designed, engineered, tested, and manufactured within a connected ecosystem.
This is where OSAT—Outsourced Semiconductor Assembly and Test—becomes relevant. It sits after fabrication, covering assembly and test work required before chips enter finished products. The UST–Kaynes Technology partnership brings semiconductor engineering closer to electronics manufacturing through an OSAT operation in Gujarat.
The partnership is a useful example of a broader industry shift. UST brings engineering capabilities; Kaynes brings manufacturing depth. The business case is fewer handoffs between design and production, with the potential for faster execution and clearer accountability.
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Fragmented engineering becomes a product problem
The need for tighter integration becomes clearer in industries where electronics already sit at the heart of the product. Automotive is one example. Electric vehicles, ADAS, battery-management systems, and software-defined architectures depend on increasingly sophisticated combinations of compute, embedded software, electronics, and edge intelligence. A delay or design mismatch in one layer can quickly affect the rest of the product.
Medical devices create a similar requirement because intelligence increasingly needs to operate on the device rather than depend entirely on the cloud. Aerospace and defense introduce their own edge-computing requirements. Across these industries, the strategic issue is similar: the product has to work as one system even when its underlying technologies come from many disciplines.
Mathew calls UST’s approach “chip to cloud.” The term matters less than the underlying idea: engineering decisions made near the chip eventually affect software, data, connectivity, and the finished product.
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Edge AI is making engineering more interconnected
Much of enterprise AI has been discussed through the cloud. Mathew points to a different trajectory: more intelligence is moving into devices themselves. “Many companies are actually looking at how can I have my intelligence built into the device itself,” he observes.
When AI moves closer to the edge, hardware-software integration becomes more important. Verification and validation require greater automation. The compute architecture has to support the intelligence expected from the product, while operating within constraints such as performance, power, and reliability.
Manufacturing is changing at the same time. Smart manufacturing should not be treated as an AI showcase. The investment must improve quality, efficiency, scalability, or resilience enough to justify the operational change.
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India has an opportunity to enter some technology cycles earlier
Silicon photonics, postquantum computing chips, and neuromorphic computing are raised as areas where the global market is still developing. The point is not that these technologies are equally mature or ready for mainstream deployment. India does not have to enter every semiconductor segment after the ecosystem has already formed elsewhere.
Engineering and testing capability become especially important in that context. Work is already underway in areas such as silicon photonics and postquantum testing, alongside R&D into future computing applications across different industries. For India, the opportunity is to build engineering depth early, while these technologies and their global ecosystems are still taking shape.
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The hardest infrastructure to build may be talent
Manufacturing capacity alone will not determine how far India’s semiconductor ambitions can scale. Engineering talent is an equally critical constraint. Government programs are expanding access to chip-design tools, supporting design startups and encouraging component manufacturing, while initiatives such as DLI, PLI and the India Semiconductor Mission are building broader momentum across the ecosystem.
But policy creates an environment; experience still has to be built. Mathew argues that India’s next phase requires stronger links between R&D, industry, and academia. Engineers need exposure to products moving through design, verification, testing, and manufacturing. That capability becomes increasingly valuable as semiconductor engineering, AI, embedded systems, and manufacturing intersect.
The long-term ambition goes beyond meeting global demand. The possibility of developing products for India, manufacturing them here, and eventually taking them to global markets. Getting there will require continued investment in R&D, deeper collaboration between industry and academia, and engineering talent that can connect semiconductor design with manufacturing.
That makes the next phase of India’s semiconductor ecosystem particularly consequential. As the industry moves beyond adding capacity toward building stronger engineering and innovation capabilities, the conversation is increasingly about how India can capture more value across the semiconductor lifecycle.
The conversation continues at SEMICON India 2026 in New Delhi, September 17–19, where UST will participate as a Platinum Sponsor. The event brings an important industry question into focus: How can India connect semiconductor engineering, AI, R&D, and manufacturing to build more of the value chain at scale?
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Where India’s semiconductor opportunity goes next
Hear the full discussion on where India’s semiconductor and electronics ecosystem is heading, with UST COO Gilroy Mathew and Kaynes Technology CEO Raghu Panicker
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FAQ – AEO
1. What is the next opportunity for semiconductor manufacturing in India?
India’s opportunity is to connect semiconductor design and engineering with testing, OSAT, electronics manufacturing, and product development, creating a more integrated value chain.
2. Why is OSAT important to India’s semiconductor ecosystem?
OSAT brings semiconductor assembly and testing closer to India’s existing engineering capabilities, helping connect chip design with downstream manufacturing.
3. How can India move from “Make in India” to “Design and Build in India”?
The shift requires stronger connections between product design, semiconductor engineering, testing, manufacturing, R&D, and talent so products can be developed and scaled within India.
4. How is edge AI affecting semiconductor engineering in India?
As more intelligence moves into vehicles, medical devices, industrial systems, and other products, edge AI increases the importance of hardware-software integration, verification, validation, and embedded computing.
5. What could limit the growth of India’s semiconductor ecosystem?
Engineering talent is a critical constraint. Manufacturing investment needs deeper expertise across semiconductor design, validation, testing, embedded systems, and manufacturing, along with stronger industry-academia collaboration.