Hyperlume

High-Level Overview

Hyperlume is a deep-tech startup founded in 2022 in Ottawa, Canada, that developed microLED-based optical interconnects to address energy consumption and bandwidth limitations in AI data centers and high-performance computing (HPC) systems.[1][2][3][4] The company targeted hyperscalers and AI infrastructure providers by replacing inefficient copper wires with light-based data transfer via waveguides, enabling higher bandwidth, lower latency, lower power use, reduced cooling needs, and smaller carbon footprints.[1][3][4] Hyperlume raised a $12.5 million oversubscribed seed round in February 2025, led by BDC's Deep Tech Venture Fund and ArcTern Ventures, with participation from MUUS Climate Partners, SOSV, Intel Capital, and LG Technology Ventures, before being acquired by Credo (NASDAQ: CRDO) to bolster AI connectivity solutions.[3][5][6]

Origin Story

Hyperlume was co-founded in 2022 by Mohsen Asad (CEO) and Hossein Fariborzi (CTO), experts in optical communication and semiconductors, to tackle connectivity bottlenecks in accelerated computing and AI data centers.[3][5] The idea emerged from the limitations of traditional copper interconnects, which waste energy as heat and cap data transfer speeds between microchips and memory in datacenters.[4] Early traction came via accelerators like Creative Destruction Lab and SOSV's HAX program in 2023, where their technical expertise secured initial investment and validation for microLED-powered optical links.[2][5] This momentum led to the landmark seed funding in 2025 and eventual acquisition by Credo.[3][5]

Core Differentiators

Hyperlume stood out in the optical interconnect space through these key advantages:

• MicroLED-based optical technology: Used ultra-fast microLEDs and low-power circuitry for pluggable, mid-board, and co-packaged optics, delivering superior bandwidth, latency, and energy efficiency over copper interconnects.[1][3][4][5]
• Energy and space savings: Reduced heat generation, easing cooling demands, shrinking datacenter footprints, and lowering carbon emissions while packing more compute units for AI/ML workloads.[4][5]
• AI/HPC focus: Tailored for chip-to-chip communication in data centers, edge computing, and next-gen processors, outperforming competitors like Delta Networks or Christie Digital in power and speed for hyperscale environments.[1][2]
• Rapid commercialization path: Backed by strategic investors like Intel Capital and LG, with plans to scale R&D and engineering post-seed funding.[3]

Role in the Broader Tech Landscape

Hyperlume rode the explosive growth of AI workloads and hyperscale datacenters, where traditional electronic interconnects face insurmountable energy and bandwidth constraints amid surging data demands.[5][6] Its timing aligned perfectly with the 2025 AI infrastructure boom, as providers sought sustainable scaling solutions to cut power costs and emissions—critical as datacenters consumed ~2-3% of global electricity and AI training models ballooned in scale.[4][5] Market tailwinds included investor fervor in deep-tech optics (e.g., seed from BDC, Intel) and the shift to optical alternatives for co-packaged systems.[3] By pioneering microLED interconnects, Hyperlume influenced the ecosystem via its Credo acquisition, accelerating industry-wide adoption of efficient, light-based connectivity to sustain AI's exponential compute needs.[5][6]

Quick Take & Future Outlook

Post-acquisition by Credo, Hyperlume's technology integrates into a comprehensive connectivity platform, positioning it to power next-gen AI networks with enhanced efficiency and scalability.[5][6] Expect accelerated deployment in hyperscale datacenters, driven by trends like AI model proliferation, edge AI expansion, and sustainability mandates, potentially slashing energy use by orders of magnitude in optical links.[3][4][5] Credo's resources will evolve Hyperlume's influence from startup innovator to core enabler of sustainable AI infrastructure, redefining chip-to-chip communication as datacenter demands intensify. This deal underscores deep-tech's path: solve critical bottlenecks to fuel the AI revolution.[5][6]