iPronics integrates Ansys solutions across its core development workflow – from optical layout to packaging and thermal simulations – enabling robust, full-stack design and validation of photonic integrated circuits (PICs) that perform reliably despite fabrication variability. These resilient components are foundational for energy-efficient, low-latency future data centre interconnects essential to AI workloads.
“The scale and traffic demands of modern data centres require greater reliability through innovative networking architectures, systems, and components,” said Daniel Pérez López, Co-Founder and CTO of iPronics. “As data centre outages increasingly impact end applications, technologies like optical circuit switching are emerging as essential to next-generation AI infrastructure. At iPronics, we develop reliable, cost-effective photonic chip switching solutions. Our work with Ansys accelerates our development cycles and enhances system reliability, enabling us to deliver cutting-edge high circuit density optical engines optimised for AI workloads – from optical cores to electronics and thermal packaging.”
Through the collaboration, Ansys expands its reach into the rapidly evolving photonics industry by supporting a real-world, production-grade customer use case.
“We’re looking forward to collaborating with iPronics to drive innovation in optical networking,” said Sanjay Gangadhara, Senior Program Director at Ansys. “Their work in reconfigurable, high-performance photonics highlights the power of Ansys simulation technologies. Together, we’re helping shape the infrastructure that will support tomorrow’s AI workloads with extended reliability and performance.”
As AI models grow in complexity and demand higher data throughput, traditional electronic interconnects are increasingly strained by latency, power, and scalability limitations. iPronics’ silicon photonics approach, supported by Ansys simulation, offers a new path forward – delivering programmable, fabrication-tolerant components that scale efficiently across hyperscale deployments.
