Ebrahim Hussain is Co-Founder of Architect Labs, where he is building AI-powered systems to accelerate semiconductor design and engineering. He brings deep expertise in AI and hardware development, with a focus on transforming how advanced chips are designed and brought to market.
Aaditya (Aadi) Subedi is Co-Founder of Architect Labs, where he is helping develop AI-native tools that streamline chip design and verification. His work centers on applying cutting-edge AI technologies to modernize semiconductor development and accelerate innovation across the compute stack.
Tell us about your company?
Architect Labs is building an AI system that designs and verifies custom chips end-to-end. Our mission is to make world-class silicon design accessible to any organization with a demanding workload, not just the handful of companies that can afford to build large in-house semiconductor teams. We believe the future of computing will be defined by custom hardware, and we’re building the infrastructure to dramatically accelerate how that hardware gets created.
What problems are you solving?
Today, designing a chip is one of the most difficult and resource-intensive engineering efforts in technology. It can take years, cost hundreds of millions of dollars, and requires highly specialized expertise that is increasingly scarce. At the same time, AI, robotics, defense, cloud infrastructure, and other industries are demanding more specialized hardware than ever before.
We’re solving the mismatch between the growing need for custom silicon and the industry’s limited ability to produce it. Our AI system is designed to automate and accelerate major parts of the chip design and verification process, enabling organizations to move from workload requirements to production-ready silicon much faster than traditional approaches allow.
What application areas are your strongest?
We’re focused on workloads where hardware has become a strategic bottleneck. That includes AI training and inference infrastructure, data center systems, networking, robotics, autonomous systems, edge computing, and other compute-intensive applications where performance, efficiency, and cost matter at scale.
More broadly, we’re interested in any domain where custom silicon can unlock meaningful advantages over general-purpose hardware.
What keeps your customers up at night?
Our customers are under pressure to deliver more compute, better performance, lower power consumption, and improved economics—all while operating within increasingly constrained hardware environments.
Many organizations recognize that custom silicon could provide a competitive advantage, but they’re concerned about the risks: lengthy development cycles, enormous upfront investment, talent shortages, and the possibility of spending years on a design that ultimately doesn’t meet expectations. They want a path to custom hardware without having to become semiconductor companies themselves.
What does the competitive landscape look like and how do you differentiate?
There are a number of companies applying AI to portions of the semiconductor workflow, whether that’s verification, EDA tooling, or specific design tasks. Our view is that the opportunity requires a much more comprehensive approach.
We’re building an end-to-end AI system for chip design and verification rather than point solutions that optimize individual steps. Our team combines deep expertise in both frontier AI research and production silicon development, which allows us to rethink the design process from first principles. Ultimately, we want to make custom silicon accessible through a much simpler interface: organizations define the workload they care about, and our system helps generate the hardware optimized for it.
What new features/technology are you working on?
Our current focus is advancing the capabilities of our AI system across the chip development lifecycle, including architecture exploration, design generation, verification, and optimization.
Longer term, we see a future where hardware and software are co-designed together. We’re investing in technologies that connect silicon design with compilers, runtimes, systems software, and eventually AI models themselves, enabling tighter optimization across the entire computing stack.
How do customers normally engage with your company?
Today, we work closely with a select group of partners that have their own chip programs, or are exploring custom solutions that off-the-shelf hardware cannot solve. For companies, with an existing chip program, we co-design silicon alongside them to dramatically accelerate their chip development timelines. For companies exploring custom silicon, the engagements typically begin by understanding the workload, performance requirements, and deployment constraints, then collaborating to evaluate how purpose-built silicon could improve outcomes.
Over time, our goal is to make custom silicon significantly more accessible, allowing many more organizations to leverage specialized hardware without needing a chip design team. This will allow companies to co-evolve their models, and software together with the underlying hardware, accelerating the industry’s path to superintelligence.
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