Deeptech Photonics
Solinide Secures €4M for AI Photonic Chips
Swedish deeptech company Solinide Photonics has raised €4 million in seed funding. The investment will accelerate the commercialisation of its silicon nitride photonic integrated circuit technology, targeting AI data centres and preparing for scalable manufacturing.
№ 78 · Friday, 21 August 2026
Solinide Photonics secured €4 million in seed funding. This investment, reported by Solinide closes €4M to commercialise photonic chips for AI data centres, will advance the commercialisation of the company’s silicon nitride photonic integrated circuit (PIC) technology. The primary focus is on AI data centres, with a secondary aim to prepare for scalable manufacturing processes.
The demand for high-performance, energy-efficient hardware for artificial intelligence continues to drive investment in next-generation computing solutions. Conventional electronic processors face bandwidth and energy efficiency constraints, particularly for large-scale, high-concurrency AI tasks.
Photonic integrated circuits offer a promising alternative, leveraging the inherent advantages of light, such as high bandwidth, low latency, and superior energy efficiency. Projects like CoMiPCE are actively researching coherent microcomb-enabled integrated photonic convolution engines specifically for energy-efficient AI, aiming to overcome the limitations of traditional von Neumann architectures.
Solinide's focus on silicon nitride PICs places it within a rapidly evolving field. Silicon nitride is a versatile platform for integrated photonics, enabling the manipulation of light on a chip. This technology is also critical in other advanced applications, such as the QPIC1550 project, which is developing quantum photonic integrated circuits at 1550 nm by integrating various components on SiN PICs for quantum communication and computing.
What this means: This funding round underscores continued investor confidence in deeptech solutions that address the escalating computational and energy demands of AI. It highlights a strategic shift towards photonic hardware to enhance processing capabilities and sustainability in AI infrastructure.
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