Could you please tell us about SiMa.ai and the core vision behind the company?

SiMa.ai was born out of a very simple observation - a lot of companies wanted to bring machine learning into real-world, physical environments, but the solutions available were either too complex, too power-hungry, or not really built for the constraints of embedded systems. 

At SiMa.ai, we deliver the industry’s first purpose-built, software-centric platform for physical AI, which includes our flagship MLSoC Modalix devices and Palette SDK. In simple terms, we provide both the hardware and the software needed to run high-performance machine learning directly on devices operating in the physical world, whether that’s robotics, industrial automation, automotive, or computer vision applications. What makes our approach different is that we focus on making ML deployment effortless.  

Customers shouldn’t need a steep learning curve or have to throw away their existing systems to adopt AI. Our platform lets them preserve legacy applications while gradually future-proofing their products with scalable machine learning. Ultimately, our mission is to disrupt the embedded market by replacing outdated technology with ML solutions that are powerful, efficient, and practical to deploy at scale. 

SiMa.ai positions itself as a physical AI company rather than a traditional AI or semiconductor firm. How would you describe the company’s core purpose, and what gap did you see in the market that led to its creation? 

We don’t see ourselves as just another AI company or a traditional semiconductor firm. Our purpose sits at the intersection of both. SiMa.ai exists to make machine learning work in the physical world, where real devices operate under real constraints like power, latency, cost, and reliability. Most AI breakthroughs over the last decade have been driven by the cloud, backed by massive compute. But deploying that same intelligence inside a factory, a vehicle, a robot, or a camera system is a completely different challenge. 

We saw a clear gap: companies wanted the benefits of ML, but without the complexity. They didn’t want to rip and replace existing systems, and they needed high performance without sacrificing energy efficiency. Legacy SoCs were never designed for ML workloads, and many AI accelerators weren’t built for practical embedded deployment. 

That’s why we built SiMa.ai from the ground up. Our purpose-built, software-centric platform helps customers transition into physical AI seamlessly, while preserving legacy applications. Our mission is simple: make machine learning scalable, effortless, and usable in the real world, not just in data centers. 

The AI industry has largely been cloud-driven so far. What is driving the shift towards edge and physical AI, and how prepared are industries to adopt AI that operates directly within machines? 

The shift is being driven by a simple reality: the most important AI applications don’t live in the cloud, they live in the physical world. Industries want intelligence inside machines, whether it’s a robot on a factory floor, a camera in a smart city, or an autonomous vehicle. In these environments, sending data back and forth to the cloud adds latency, increases cost, and raises privacy and reliability concerns. 

That’s why physical AI is becoming crucial. It enables real-time decision-making directly at the source, where the action happens. Industries are absolutely ready for this transition. The demand is already there. What they’ve been waiting for are solutions that are practical, energy-efficient, and easy to deploy without replacing existing systems. We’re now at a point where the technology is catching up with the need, and adoption is accelerating quickly across manufacturing, automotive, and industrial automation. 

Your partnership with Kaynes Semicon places strong emphasis on ‘Make in India’ electronics. How important is local manufacturing and ecosystem collaboration to SiMa.ai’s long-term strategy, particularly for mission-critical and defence applications? 

Local manufacturing and ecosystem collaboration are absolutely central to SiMa.ai’s long-term strategy, especially in mission-critical and defence domains. Physical AI is all about trust, reliability, and deployment at scale. For sectors like aerospace and defence, having a secure, resilient, and locally anchored electronics supply chain becomes essential. Additionally, defense applications are size, weight and power (SWAP) constrained, so our solution is able to meet these critical requirements and ensure customers retain their advantage. 

That’s why our partnership with Kaynes Semicon is so important. India has world-class engineering talent and a rapidly growing semiconductor and electronics manufacturing base. By combining SiMa.ai’s MLSoC Family devices and Palette SDK & LLiMa software packages with Kaynes’ advanced assembly, testing, and manufacturing capabilities, we can deliver truly “Make in India” systems that meet the highest requirements for smart vision, robotics, surveillance, and autonomous defence applications. 

This collaboration also helps customers move faster, from proof-of-concept to real-world commercialisation, through production-ready reference designs and scalable manufacturing. 

What were the key strategic drivers behind SiMa.ai’s partnership with Kaynes Semicon, and how does this collaboration strengthen your ability to deliver physical AI solutions for defence and industrial applications? 

The partnership with Kaynes Semicon was driven by two clear priorities: scaling physical AI adoption and building trusted, production-ready systems in India. 

Kaynes brings deep expertise in semiconductor assembly, testing, and defence-grade electronics manufacturing, which perfectly complements SiMa.ai’s purpose-built, software-centric platform for physical AI. Together, we can deliver “Make in India” physical AI solutions that meet the performance, reliability, and security requirements of mission-critical sectors like defence, aerospace, industrial automation, and robotics. 

This collaboration also helps customers move faster from evaluation to deployment through reference designs and volume manufacturing readiness. 

SiMa.ai works with defence and industrial sectors where reliability and security are critical. How does your physical AI platform meet these on-ground, mission-critical requirements? 

In defence and industrial environments, AI has to work every time, in real-world conditions, with no room for failure. That’s exactly what our platform is built for. SiMa.ai’s MLSoC Family devices deliver high-performance machine learning with low power, low latency, and the reliability needed for mission-critical systems like smart vision, surveillance, robotics, and vehicle autonomous operations. 

We also designed the platform to be practical for deployment, allowing customers to preserve legacy applications while gradually integrating ML capabilities. This makes adoption faster, more secure, and future proof - all while reducing total cost of ownership. Ultimately, physical AI in these sectors is about trust, efficiency, and real-time decision-making at the machine level, and that is where SiMa.ai is focused. 

Defence and aerospace place unique demands on reliability, security and latency. How does co-developing solutions with Kaynes Semicon strengthen SiMa.ai’s ability to address mission-critical physical AI applications in these sectors? 

Defence and aerospace applications demand the highest levels of reliability, security, and real-time performance. Latency is not just a technical metric, it can be mission-critical. 

Co-developing with Kaynes Semicon significantly strengthens our ability to meet these requirements. Kaynes brings proven expertise in defence-grade electronics, advanced semiconductor assembly and testing, and manufacturing systems built for stringent operational environments. By combining that with SiMa.ai’s purpose-built, software-centric platform for physical AI, we can deliver solutions that are not only high-performance and energy-efficient, but also production-ready, trusted, and scalable. This partnership allows us to move faster from innovation to deployment, while building secure, “Make in India” systems for next-generation surveillance, autonomous defence platforms, and aerospace capabilities. 

India is emerging as both a manufacturing base and an innovation hub for advanced electronics. How do you see India’s role evolving in SiMa.ai’s global growth story over the next few years? 

We see India not just as a manufacturing base, but as a true innovation hub for physical AI. The country has a unique combination of world-class engineering talent, a rapidly expanding electronics ecosystem, and strong national momentum through initiatives like “Make in India” and Atmanirbhar Bharat. 

Over the next few years, India will be central to how we scale, both in terms of developing next-generation mission-critical applications and building production-ready systems for global markets. That’s why we’re actively building deep ecosystem partnerships here, including collaborations with leaders like L&T, the Maini Group, and now Kaynes Semicon. Together, these partnerships accelerate the global adoption of physical AI across industrial automation, mobility, aerospace, and defence. 

Ultimately, we believe India will be a key force in shaping the future of embedded intelligence worldwide, and SiMa.ai is committed to being part of that journey.