Delos Data raises $100 million to link AI chips in data centers.
chips funding startup
| Source: Techmeme | Original article
Delos Data, an Intel‑veteran startup that builds network chips and software to connect AI chips, announced a $100 million funding round from Matrix, Playground and Socratic Partners.
Delos Data, a semiconductor startup founded by former Intel engineers, announced on Tuesday that it has closed a $100 million financing round led by Matrix, Playground and Socratic Partners, with participation from Capricorn’s Technology Impact Fund, Matter Venture Partners and IAG. The capital will be used to bring its “Nonstop AI” networking architecture – a combination of custom chips and orchestration software – to market.
The firm’s technology targets the inter‑chip fabric that links AI accelerators inside modern data centres. By replacing traditional static topologies with a switched‑mesh that can reroute traffic on‑the‑fly, Delos promises lower latency, higher resiliency and easier scaling as AI workloads grow. Its software platform also streamlines configuration and monitoring of these fabrics, offering AI chip makers a faster path to rack‑scale deployment.
The raise comes at a time when the AI hardware ecosystem is racing to solve the “data‑movement” bottleneck that threatens to curb the performance gains of ever larger models. Competitors such as Nvidia, AMD and emerging fabless players are all courting data‑centre operators with proprietary interconnects, while cloud providers are investing in massive new facilities. Delos’s approach could give AI chip startups a more open, vendor‑agnostic option, potentially reshaping how Nordic and global data centres are built.
Investors will be watching how quickly Delos can move from design to silicon tape‑out and whether it secures early customers among AI accelerator vendors. Follow‑on funding, partnership announcements, and the first silicon samples – expected later this year – will indicate whether the startup can translate its architecture into a commercially viable alternative to existing AI networking solutions.
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