❯ AI chip IP company Velaura closes $110M Series A, valuation tops $1B

WATT ANGLEVelaura AI has closed a $110 million Series A at a post-money valuation above $1 billion, led by Seligman Ventures. It doesn’t build entire chips; it sells digital-chip IP and a companion design platform. Customers integrate its modules into their own AI accelerators to get the same compute at lower power. Its flagship product, Titan Core, targets conventional accelerator designs, and the company claims 2–4x performance per watt.

MODULE TO PLATFORMThis is a Silicon Valley company whose founding date isn’t disclosed in public materials; it previously existed mainly as an IP supplier. The change comes from the demand side: the bottleneck in AI data centers has shifted from compute to electricity. Per-rack power keeps climbing, electricity bills and cooling are beginning to determine deployment scale, and only now has energy efficiency gone from an engineering metric to a procurement criterion. Velaura only launched Titan Core as a standalone platform this year, and the funding followed right behind. The investor roster shows who it wants to sell to: beyond the lead, new backers include Capricorn Investment Group and Prosperity7 Ventures, while existing shareholders Mayfield, Maverick Silicon, MARA, Premji Invest, Samsung Catalyst Fund and StepStone Group all followed on. Samsung and crypto-mining company MARA sit at the two ends of the spectrum — advanced process nodes and power-dense deployments, respectively.

TAPE-OUT RECORDThe hardest gate in the IP business is whether customers believe you can ramp to volume production. Velaura’s proof is more than 30 million ASICs: its underlying technology has already shipped at commercial scale across multiple advanced process nodes, with a proven record on yield and reliability — not simulation data. That sets it apart from most low-power startups that only have lab results. The team comes from Apple, Nvidia, Google, Qualcomm and Marvell; co-founder and CEO Rajiv Khemani has spent decades in the semiconductor industry. It’s betting on two markets at once: hyperscale data centers on one side, and so-called physical AI — robots, drones and autonomous systems — on the other. The latter is even more power-sensitive than data centers; the battery is only so big. The round’s proceeds will go to accelerating product commercialization, expanding engineering and customer teams, and pursuing joint development with strategic customers.

POWER BILLS DECIDEA $1 billion valuation for an IP company that hasn’t yet delivered at scale rests on the view that energy efficiency is becoming the hardest constraint in AI infrastructure. Capital is starting to pay separately for performance per watt — two years ago, that wouldn’t have gotten its own line item. The beneficiaries are upstream suppliers that can bend the power curve down; the pressure falls on compute operators that scale by piling on cards and power. When electricity supply can’t keep up, whoever’s chip uses less power can pack more compute into the same rack. The capacity metric for data centers needs to change: it used to be counted in GPUs; going forward, it’s counted in available power.

▪ SIGNALThe ceiling on compute expansion is shifting from chip supply to power supply. Energy efficiency has already gone from an engineering metric to a price line on the procurement list.