In a daring step forward for semiconductor technology, Cognichip has launched out of stealth with $33 million in seed funding to construct what it calls Artificial Chip Intelligence (ACI®) — a foundational shift in how chips are designed, developed, and dropped at market. The funding round was led by Lux Capital and Mayfield, with participation from FPV and Candou Ventures.
The San Francisco-based startup is taking aim on the two largest barriers in chip design: prohibitive cost and time. With development cycles often exceeding 3–5 years and $100 million per chip, innovation within the semiconductor space has slowed dramatically. Founded by industry veteran Faraj Aalaei — who previously took two semiconductor firms public and served as CEO of Centillium Communications — Cognichip plans to alter that.
What’s Artificial Chip Intelligence (ACI®)?
At the guts of Cognichip’s platform is a physics-informed AI foundation model purpose-built for semiconductor design — a pointy departure from traditional tools and processes. Dubbed ACI®, this latest system introduces “designer-level cognitive abilities” to AI, enabling it to know, learn from, and optimize your entire chip development process with human-like reasoning and physics-awareness.
This model doesn’t simply automate workflows — it redefines them. By embedding AI deep into the physics of semiconductor systems, ACI® can analyze global and native variables concurrently, design components in parallel, and perform constraint-aware optimizations across the chip stack. This conversational design approach replaces the rigid, serial processes which have constrained the industry for many years.
Key performance goals for ACI® include:
- 50% reduction in development time: Because of parallelized, AI-driven design cycles
- 75% reduction in cost: By minimizing engineering labor and testing redundancy
- Smaller, more efficient chips: Through real-time optimization of power, performance, and area (PPA) metrics
- Greater adaptability: ACI® enables rapid design variation, supporting smaller, more specialized chips
Why This Matters Now
Despite AI’s exponential rise, semiconductor innovation has lagged. While generative AI models will be deployed in weeks, designing the chips they run on still takes years. This disconnect has bottlenecked hardware advancement and discouraged latest entrants.
Cognichip is confronting this head-on. Its technology allows engineers to give attention to innovation relatively than infrastructure, enabling anyone from major enterprises to startup teams to bring latest chips to market — faster, cheaper, and with less expertise required.
Faraj Aalaei, CEO and Founder, explains:
A Veteran Team, a Modern Mission
Cognichip’s founding team is a who’s who of AI and semiconductor veterans:
- Ehsan Kamalinejad, Co-founder & CTO: Led Apple’s AI features (like Photo Memories) and pioneered reinforcement learning at AWS
- Simon Sabato, Co-founder & Chief Architect: Former lead architect at Google, Cisco, and Cadence
- Mehdi Daneshpanah, VP of Software: Ex-head of world software at KLA
- Stelios Diamantidis, Chief Product Officer: Creator of Synopsys’ AI-driven DSO.ai platform
Supporting them is a deep bench of PhDs from MIT, Stanford, Berkeley, and the University of Toronto, together with Olympiad medalists in math and physics. This interdisciplinary team is constructing what could turn into the world’s first true cognitive engine for chip creation.
From Bottleneck to Breakthrough
Cognichip doesn’t just aim to enhance chip design — it seeks to democratize it. With AI handling a lot of the complexity, small startups and research teams could soon design chips previously reserved for multibillion-dollar firms.
This has enormous implications for:
- AI infrastructure, where customized accelerators are increasingly needed
- Healthcare, which demands low-power, high-efficiency chips for wearables and diagnostics
- Energy, where optimization of compute-per-watt is mission-critical
- Autonomous systems, which require domain-specific silicon at scale
Investors see it as greater than a bet on higher chips — they see it as a shift within the innovation stack for your entire tech ecosystem.
said Navin Chaddha, Managing Partner at Mayfield.
The Road Ahead: AI Chips, Reinvented
The semiconductor industry stands at a pivotal crossroads. As generative AI systems push the bounds of compute demand, there is a growing consensus that traditional chip design methods can not keep pace. Major tech firms are actually racing to develop AI-specialized chips — from inference-optimized accelerators to domain-specific processors for edge computing, robotics, and energy-efficient datacenters.
Nevertheless, the bottleneck stays not in fabrication, but in design. Developing these latest chips still requires years of engineering effort, massive capital investment, and deep domain expertise — barriers that exclude all but the most important players. This mismatch between the speed of AI model development and the pace of chip design is making a widening gap within the innovation stack.
Cognichip‘s vision is to shut that gap. By introducing ACI®, the corporate is laying the inspiration for a brand new era where AI doesn’t just eat compute — it actively contributes to creating it. This shift could empower a brand new wave of hardware innovation, unlocking faster, cheaper, and more tailored chips for all the pieces from personalized medical devices to next-gen autonomous systems.
Because the industry moves toward trillion-parameter models and real-time AI at the sting, the demand for agile, optimized, privacy-conscious chips will only speed up. Cognichip is positioning itself at the middle of this transformation — not by making chips faster, but by making chip creation itself intelligent, accessible, and exponentially more scalable.
On this latest paradigm, the excellence between software and hardware blurs, and crucial breakthroughs may come not only from latest algorithms — but from the machines that design the machines.
