EFFECT Photonics Secures $62 Million in Series D Funding

2 min read
EFFECT Photonics Secures $62 Million in Series D Funding

EFFECT Photonics, a provider of coherent optical solutions for data center and edge networks, announced the closing of its Series D funding round. The round totaled $62 million. The company develops energy-efficient, high-performance coherent technology for demanding network environments. This technology is designed for use in data center campuses, intra-data center links, and the network edge, as coherent optics expand beyond traditional core networks. EFFECT Photonics' solutions utilize a fully fabless model and leverage strategic supply chain partnerships to meet bandwidth and power efficiency needs driven by AI infrastructure and next-generation connectivity.

"This funding milestone reinforces the strong market demand we’re seeing and allows us to execute aggressively on our roadmap," commented Roberto Marcoccia, CEO at EFFECT Photonics.

Related startups

The additional $24 million brings the total Series D funding to $62 million. This capital injection will support the company's continued growth and expansion into new markets. The funding follows significant technical and commercial advancements, enabling the next wave of high-performance networking at the edge and AI infrastructure. Further details regarding the specific allocation of funds or future plans were not disclosed in the press release. The company's technology is designed to address the increasing bandwidth and power efficiency demands of modern data networks.

Key competitors include Acacia Communications (acquired by Cisco), which offers similar coherent optical solutions, and Infinera, a major player in the optical networking market with a broad range of products. These companies also provide coherent optical technology for high-speed data transmission.

© 2025 StartupHub.ai. All rights reserved. Do not enter, scrape, copy, reproduce, or republish this article in whole or in part. Use as input to AI training, fine-tuning, retrieval-augmented generation, or any machine-learning system is prohibited without written license. Substantially-similar derivative works will be pursued to the fullest extent of applicable copyright, database, and computer-misuse laws. See our terms.