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Architect Labs raises $24M to automate chip design. Key Points * Architect Labs raised $24 million in seed funding to build an AI system that designs custom chips end-to-end, from specification to manufacturable output. * The round was led by Kindred Ventures, with TQ Ventures, Race Capital, and Together Fund participating, alongside angels from OpenAI, NVIDIA, Perplexity, SambaNova, and Google DeepMind. * The Palo Alto startup aims to make custom chip design accessible to any organization, compressing development timelines that currently take two to five years. June 18, 2026 Credits: BUSINESS WIRE Architect Labs emerged from stealth today with $24 million in seed funding and a specific goal: make world-class chip design available to any organization with a demanding workload, not just the handful of companies that can afford to build that expertise in-house. The Palo Alto startup is building an AI system that handles chip design and verification from start to finish. It was founded by Ebrahim Hussain, who started college at 15 after skipping high school and later worked on silicon at Apple and Tesla, and Aaditya Subedi, a former AI researcher at Harvard who focused on code verification. The two met at Stanford, where they researched AI systems for chip design before leaving to start the company. Demand for custom chips is growing fast and pulling in a wide range of industries. According to TrendForce, custom AI chip shipments from cloud providers are on track to grow 44.6% in 2026, compared to 16.1% for merchant GPU shipments. AI labs, governments, and large technology companies are all pursuing silicon tailored to their specific workloads. The demand is no longer limited to data centers either: robotics, autonomous vehicles, defense, spatial computing, and personal devices are all part of the picture. Yet designing a chip from scratch remains one of the slowest and most expensive processes in the technology industry. The $24 million seed round was led by Kindred Ventures, with TQ Ventures, Race Capital, and Together Fund also participating. The angel list includes Lukasz Kaiser, co-author of the "Attention Is All You Need" paper and a researcher at OpenAI; Aravind Srinivas, co-founder and CEO of Perplexity AI; Kunle Olukotun, founder of SambaNova; Trevor Blackwell, an OpenAI founding team member; and engineering leaders from OpenAI, NVIDIA, Google DeepMind, Synopsys, Keysight, and others. Kindred founder and managing partner Steve Jang joined the Architect Labs board. Why chip design has not kept pace with AI A chip typically takes two to five years to go from concept to working hardware. Before a single device exists, the investment can run into hundreds of millions of dollars. The pool of engineers who can do this work is small and concentrated in a few large companies. The software tools used to design chips, called EDA tools, were built decades ago for workflows that assumed humans would be doing most of the work. Some companies have tried to speed up the process by adding AI tools on top of those existing workflows. Architect Labs takes a different view. The company argues that bolting AI onto a decades-old process produces limited results. Instead, it is building a new design flow from scratch, one where AI is involved at every stage: from the initial specification through architecture decisions, logic design, verification, and the final layout that goes to manufacturing. How Architect Labs plans to spend the funding The seed capital will go toward expanding the company's computing infrastructure, continuing AI research, and working directly with early partners to produce real chips. Architect Labs says it has already deployed its technology with semiconductor companies, and AI-generated designs are expected to tape out, meaning go through the manufacturing process, on leading-edge foundry nodes before the end of this year. The company's longer-term plans extend beyond chip design itself. Architect Labs intends to get involved in the software layers that sit above the hardware: compilers, runtimes, and system software. Eventually, it aims to co-optimize AI models alongside the chips built to run them, so hardware development and model development can inform each other rather than proceed independently. "We are just now entering into an era of custom chips for various systems and workload types. To achieve this ideal diversity of AI infrastructure, research labs, software platforms, robotics makers, and cloud operators all need to be able to iterate on novel chip hardware at the same pace and creativity as model development. Using AI for chip co-design, Architect Labs proposes to deliver on this vision of ultra-low latency, energy-efficient, and affordable intelligence at scale." - Steve Jang, founder and managing partner of Kindred Ventures What Architect Labs actually does The company works as a design partner, not a software tools provider. It does not sell EDA software to chip engineers. Instead, it works directly with semiconductor companies, AI labs, software platforms, and national programs, taking a description of a workload and producing a full chip design to match. Architect Labs is incorporated as Architect Silicon Inc. and is based in Palo Alto. The team has practical experience across the semiconductor industry. Head of hardware Vipin Boyanapalli was a senior director in Intel's Data Center Division, where his team ran over $10 billion in product lines. Kevin Lin, head of AI, previously led Trust and Safety ML at Anthropic. Ekin Sumbul, head of IP, comes from research roles at Meta Silicon and Intel AI Labs. Across the team, members have taped out more than 80 production chips and include engineers who worked on one of the first neuromorphic chips, a type of processor modeled on the structure of the brain, at Intel. "AI models have advanced dramatically across nearly every field, yet chip development cycles remain equally slow and painful. Unlocking AI-first semiconductor design requires a first-principles rethink of the entire design process, not forcing AI agents into workflows that were never built for them." - Ebrahim Hussain, co-founder of Architect Labs To explain what it is trying to do, Architect Labs points to what happened in semiconductors roughly three decades ago. TSMC and the rise of fabless chip companies separated design from manufacturing, which let businesses like NVIDIA, Broadcom, and Apple design chips without ever building a factory. Architect Labs is applying that same logic one step earlier in the process: removing the need to have in-house chip design expertise in order to get a chip built. The company calls this vision the "designless" semiconductor industry. The investors behind the Architect Labs round The round was led by Kindred Ventures, an early-stage venture firm that backs founders across technology and science. Steve Jang, Kindred's founder and managing partner, joined the Architect Labs board. Race Capital, TQ Ventures, and Together Fund also participated in the round. Among the angels and advisors are Srinivas Narayanan, former CTO of B2B at OpenAI; Dr. Alex Wissner-Gross, a computer scientist associated with MIT and Harvard; Arash Ferdowsi, co-founder of Dropbox; Siddhartha Nath of Google DeepMind; and Professor Thierry Tambe of Stanford. Funding details. * Company name: Architect Labs * Funding round: seed * Date: June 2026 * Funding amount: $24 million * Lead investors: Kindred Ventures

Architect Labs has raised $24 million in seed funding to use artificial intelligence to accelerate custom chip design. The Palo Alto-based startup aims to challenge Broadcom and Marvell, which generate tens of billions of dollars designing custom AI and computing chips for cloud companies like Amazon and Google. The company plans to reduce the chip design process, which currently takes roughly two years and costs hundreds of millions of dollars. Architect Labs will target both chip companies and software firms seeking custom chips to improve application performance. Founded by Ebrahim Hussain and Aaditya Subedi, the 18-person company aims to make chip design as accessible as TSMC has made manufacturing. The funding round was led by Kindred Ventures, with participation from TQ Ventures, Race Capital and Together Fund. Google DeepMind Chief Scientist Jeff Dean and executives from OpenAI and Nvidia also invested.