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Multiverse Computing's Series C funding validates its approach using tensor network methods from quantum physics to compress large language models for efficient edge deployment. This capital injection will accelerate R&D in sovereign AI infrastructure while scaling applications across high-compute sectors like defense and aerospace without relying on massive data centers. The move underscores a strategic shift toward making advanced AI accessible via lower-energy, device-native solutions derived from fundamental physical principles.
Multiverse Computing Announces Series C Fundraising Targeting up to $570 Million

Insider Brief PRESS RELEASE — Multiverse Computing, the global leader in efficient AI, today announced a $570 million (€500M) Series C funding round at a $1.7 billion (€1.5B) pre-money valuation, a 5x step-up from its Series B. The round is co-led by Forgepoint Capital International, BNPP SIVF, and Bullhound Capital, with additional commitments to date […]
Multiverse Computing has raised a $570 million Series C funding round at a $1.7 billion pre-money valuation to accelerate deployment of its AI model compression platform, CompactifAI, and expand its efficient AI infrastructure globally. The company’s CompactifAI technology applies tensor network methods derived from quantum physics to compress large language models by 80–95% with minimal accuracy loss, enabling faster, lower-energy AI deployment across cloud, on-premises, and edge devices. The funding will support research and development, sovereign AI infrastructure, expansion into key international markets, and scaling deployments across industries including manufacturing, finance, energy, aerospace, cybersecurity, defense, and healthcare. PRESS RELEASE — Multiverse Computing, the global…
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