Cognichip secured $60 million in Series A funding to scale its physics-informed AI platform for chip design, bringing total funding to $93 million. The round was led by Seligman Ventures with participation from SBI Investment and existing investors including Mayfield and Lux Capital. As part of the financing, Lip-Bu Tan and Umesh Padval joined Cognichip’s board, signaling strong backing from semiconductor industry veterans.
Cognichip positions its ACI® (Artificial Chip Intelligence) platform as a full-stack AI system for semiconductor design, built on physics-informed foundation models. The company targets long-standing bottlenecks in chip development, where design cycles often span years and require hundreds of millions of dollars. By integrating models, datasets, and design workflows, Cognichip aims to parallelize traditionally serial processes across digital, analog, and mixed-signal domains. The platform claims the potential to reduce design costs by up to 75% and cut timelines by 50%, while optimizing power, performance, and area.
Founded in 2024 by CEO Faraj Aalaei, Cognichip has assembled a team spanning semiconductor architecture and advanced AI research. The company reports engagements with more than 30 semiconductor firms, including several top-tier chipmakers, and is focusing on enterprise deployment across design and manufacturing workflows. Its approach contrasts with general-purpose AI tooling by emphasizing domain-specific datasets, physics-based reasoning, and integration into production design environments.
- $60M Series A led by Seligman Ventures; total funding reaches $93M
- Lip-Bu Tan and Umesh Padval join board
- ACI® platform uses physics-informed foundation models for chip design
- Targets up to 75% reduction in design costs and 50% faster development cycles
- Focus on parallelizing chip design workflows across digital, analog, and mixed-signal domains
- Active engagements with 30+ semiconductor companies, including top-tier players
“The semiconductor industry is at a critical juncture; an AI framework for innovation and efficiency will unlock massive global opportunity,” said Lip-Bu Tan, CEO of Intel.
🌐 Analysis: Cognichip’s approach reflects a broader shift toward domain-specific AI models in semiconductor design, where companies like Synopsys and Cadence Design Systems are also embedding AI into EDA workflows. The emphasis on physics-informed models suggests a move beyond LLM-based copilots toward tightly coupled design automation systems that can impact verification, layout, and manufacturability.
🌐 Analysis: The participation of Intel leadership and investors tied to firms such as NVIDIA (via Mellanox lineage) highlights increasing industry alignment around accelerating chip design cycles to keep pace with AI infrastructure demand, particularly as advanced-node complexity and costs continue to rise.
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