embedUR systems announced the launch of Edge AI platform ecosystem ModelNova alongside the establishment of a dedicated Edge Intelligence Center in Chennai with a 100-engineer capacity. The new facility will drive the development and deployment of secure, on-device intelligence across telecom, industrial, and semiconductor industries.
The launch marks a major milestone in embedUR’s Rs 500 crore investment commitment in Tamil Nadu over five years, with 2026 representing the third phase of this strategic expansion. The Chennai expansion reinforces the company’s focus on platform IP development, on-device AI systems engineering, and ecosystem enablement, in collaboration with global technology partners including STMicroelectronics, Infineon, NXP, Synaptics, Ceva, Arm, and several other leading silicon players, said the company.
Speaking at the launch, Rajesh Subramaniam, Founder and CEO, embedUR systems, shared the company’s evolution and strategic vision. Founded in 2004, embedUR began its India operations in 2008, initially focusing on software for wireless devices such as access points and internet gateways. Over time, the company expanded into embedded software development and licensed its proprietary Wi-Fi software solution, Astral, to major global service providers.
Recognizing the rapid emergence of Edge AI nearly four years ago, embedUR made early investments in what would become ModelNova, leveraging its deep relationships with leading silicon vendors. Since 2023, this initiative has evolved into a comprehensive platform ecosystem, driving partnerships with Synaptics, STMicroelectronics, Infineon, Siva, Olive, Atmosic, and Arm, among others.
ModelNova Hub now offers a curated collection of highly optimized AI models for constrained devices, while Fusion Studio serves as a one-stop platform for developers and enterprises to seamlessly train, customize, optimize, and deploy AI models directly onto hardware. This integrated approach eliminates the complexity of managing multiple AI tools and significantly lowers technical entry barriers. In parallel, embedUR has strengthened its global leadership through active participation in the World Edge AI Foundation and the Edge AI Foundation advisory board, alongside companies such as Sony, NXP, and STMicroelectronics, further cementing its leadership in the global Edge AI ecosystem. As part of its Tamil Nadu investment commitment, embedUR has already grown its workforce from 249 in early 2024 to 420 today, with plans to exceed 550 employees by the end of 2026, supported by investments in infrastructure, talent acquisition, and deep skilling programs to build AI-ready engineering teams.
Against this backdrop, Tech Achieve Media (TAM) spoke with Rajesh Subramaniam, Founder and CEO, embedUR systems, on the strategic significance of the launch, industry adoption of Edge AI, data privacy implications, and talent development.
TAM: Could you share insights into the key industry verticals and client segments adopting your edge AI applications?
Rajesh Subramaniam: Our strategy is centered around deep partnerships with leading silicon vendors such as STMicroelectronics, Infineon, Synaptics, Siva, and Arm. These collaborations allow us to support their customers by accelerating product development through our Edge AI tools and platforms. Our role is to help convert edge AI concepts into production-ready solutions using Fusion Studio and ModelNova Hub. Adoption spans multiple verticals, including industrial automation, automotive, logistics, transportation, and healthcare. AI is fundamentally data-driven, and wherever meaningful datasets exist, it enables highly scalable applications. This makes Edge AI extremely versatile, cutting across industries and use cases.
TAM: With growing awareness around data privacy and the enforcement of the Digital Personal Data Protection Act (DPDPA), how does edge AI reshape the data privacy landscape?
Rajesh Subramaniam: Edge AI is inherently aligned with privacy-first principles. Unlike cloud-based AI systems, where data is transmitted and stored remotely, edge AI processes data directly on the device, keeping it local, secure, and private. For instance, in a factory setting, anomaly detection models operate directly on sensor data collected within the factory floor. The data never leaves the premises, ensuring confidentiality and compliance. Another example is facial recognition–based access control systems. The model runs entirely on the device, without backend connectivity. Facial mappings are not stored or transmitted, making the solution highly secure and resistant to hacking. This makes edge AI ideally suited for sensitive environments such as hospitals, corporate campuses, and industrial facilities, where privacy and security are paramount.
TAM: With the Chennai expansion, you are expected to generate significant employment. Given the scarcity of AI talent, how has your hiring experience been in India, and what is your strategy going forward?
Rajesh Subramaniam: We have deep-rooted academic partnerships in Chennai and across India. Two years ago, we launched ModelNova.ai, a free platform for students and developers to gain hands-on exposure to edge AI technologies. This early exposure helps significantly reduce the learning curve. Additionally, Fusion Studio simplifies model development, allowing engineers to become productive quickly without needing deep expertise in every AI domain. This approach allows us to rapidly scale proof-of-concepts, accelerate product cycles, and expand our AI model library, effectively addressing the talent challenge.
TAM: As a closing note, what key takeaway would you like stakeholders to remember from today’s announcement?
Rajesh Subramaniam: We have built a one-of-a-kind facility that is uniquely positioned, not only in India but globally, to meet the rising demand for physical AI over the next five years. This center represents our commitment to shaping the future of real-world, production-grade Edge AI.
