Companies and governments are seeking tools to run AI locally in a bid to slash cloud infrastructure costs and build sovereign capability. Quadric, a chip-IP startup founded by veterans of early bitcoin mining firm 21E6, is trying to power that shift. The company is scaling beyond automotive into laptops and industrial devices with its on-device inference technology.
That expansion is already paying off. Quadric posted between fifteen and twenty million dollars in licensing revenue in 2025, up from around four million dollars in 2024, according to CEO Veerbhan Kheterpal. The company, based in San Francisco with an office in Pune, India, is targeting up to thirty-five million dollars this year as it builds a royalty-driven on-device AI business. This growth has buoyed the company, which now has a post-money valuation between two hundred seventy and three hundred million dollars, up from around one hundred million dollars in its 2022 Series B.
It has also helped attract investors. Quadric announced a thirty million dollar Series C round last week led by ACCELERATE Fund, managed by BEENEXT Capital Management, bringing its total funding to seventy-two million dollars. The raise comes as investors and chipmakers look for ways to push more AI workloads from centralized cloud infrastructure onto devices and local servers.
Quadric began in automotive, where on-device AI can power real-time functions like driver assistance. Kheterpal said the spread of transformer-based models in 2023 pushed inference into everything, creating a sharp business inflection over the past eighteen months as more companies try to run AI locally rather than rely on the cloud.
He stated that while Nvidia is a strong platform for data-center AI, Quadric aimed to build a similar programmable infrastructure for on-device AI. Unlike Nvidia, Quadric does not make chips itself. Instead, it licenses programmable AI processor IP, which Kheterpal described as a blueprint that customers can embed into their own silicon, along with a software stack and toolchain to run models on-device.
The startup’s customers span printers, cars, and AI laptops, including Kyocera and Japan’s auto supplier Denso, which builds chips for Toyota vehicles. The first products based on Quadric’s technology are expected to ship this year, beginning with laptops.
Nonetheless, Quadric is now looking beyond traditional commercial deployments and into markets exploring sovereign AI strategies to reduce reliance on U.S.-based infrastructure. The startup is exploring customers in India and Malaysia and counts Moglix CEO Rahul Garg as a strategic investor helping shape its India sovereign approach. Quadric employs nearly seventy people worldwide, including about forty in the U.S. and around ten in India.
This push is being driven by the rising cost of centralized AI infrastructure and the difficulty many countries face in building hyperscale data centers. This prompts more interest in distributed AI setups where inference runs on laptops or small on-premise servers inside offices rather than relying on cloud-based services for every query.
Industry analysis points to this shift, as AI inference moves closer to users and away from purely centralized architectures. Reports note that the sovereign AI approach has gained traction as policymakers and industry groups push for domestic AI capabilities spanning compute, models, and data.
For chipmakers, the challenge is that AI models are evolving faster than hardware design cycles. Kheterpal argued that customers need programmable processor IP that can keep pace through software updates rather than requiring costly redesigns every time architectures shift.
Quadric is pitching itself as an alternative to chip vendors such as Qualcomm, which typically uses its AI technology inside its own processors, as well as IP suppliers which sell neural processing engine blocks. Kheterpal said Qualcomm’s approach can lock customers into its own silicon, while traditional IP suppliers offer engine blocks that many customers find difficult to program.
Quadric’s programmable approach allows customers to support new AI models through software updates rather than redesigning hardware. This gives an advantage in an industry where chip development can take years, while model architectures shift in a matter of months.
Still, Quadric remains early in its buildout, with a handful of signed customers so far. Much of its longer-term upside is dependent on turning today’s licensing deals into high-volume shipments and recurring royalties.