Ricursive Intelligence
Category: AI Infrastructure
A frontier AI lab dedicated to automating and optimizing semiconductor design through advanced reinforcement learning, creating a recursive feedback loop between AI software and hardware. Ricursive Intelligence was founded in 2025. The company is led by Anna Goldie. Based in San Francisco, USA. Team size: 1-10. Total funding raised: $300M (Series A at $4B valuation). Latest round: Series A ($300M, Jan 2026) at $4B valuation. Key investors include ["Sequoia Capital","Radical Ventures","Lightspeed Venture Partners","DST Global","Striker Venture Partners"].
- Founded
- 2025
- Headquarters
- San Francisco, USA
- Team size
- 1-10
- Total funding
- $300M (Series A at $4B valuation)
Value proposition
Drastically reduces chip design cycles from months to hours while optimizing for power, performance, and area (PPA) by leveraging AI to solve complex physical design challenges.
Products and solutions
["AI-driven Chip Floorplanning Engine","Reinforcement Learning Frameworks for Hardware Optimization","Automated Semiconductor Layout Tools","Recursive AI-Hardware Co-design Platform"]
Unique value
Founded by the creators of AlphaChip (Google DeepMind), the team is the first to successfully apply deep reinforcement learning to production-grade semiconductor floorplanning at scale.
Target customer
Semiconductor manufacturers, fabless chip designers, hyperscale cloud providers, and AI hardware engineering firms.
Industries served
["Semiconductors","Artificial Intelligence Infrastructure","Cloud Computing","High-Performance Computing (HPC)"]
Technology advantage
Proprietary 'recursive' approach where AI models are used to design the next generation of chips that will, in turn, run more powerful AI models, breaking the traditional compute bottleneck.
How they differentiate
Founded by the original creators of AlphaChip, the company utilizes proprietary reinforcement learning to automate semiconductor floorplanning, reducing design cycles from months to hours while creating a 'recursive' loop where AI-designed chips accelerate the next generation of AI models.
Main competitors
["Synopsys (DSO.ai)","Cadence Design Systems (Cerebrus)","Google DeepMind (AlphaChip)"]
Key partnerships
["Sequoia Capital","Radical Ventures","Lightspeed Venture Partners","DST Global","Stanford University (Academic/Research ties)"]
Notable customers
["Stealth-mode partnerships with major hyperscale cloud providers","Tier-1 semiconductor manufacturers"]
Major milestones
["Emerged from stealth in January 2025 led by former Google DeepMind and Anthropic researchers.","Secured $300M Series A at a $4B valuation in January 2025.","Established a recursive AI-hardware co-design platform to solve the global compute bottleneck."]
Growth metrics
Achieved a $4 billion valuation within two months of public launch, reaching 'unicorn' status faster than almost any other AI startup in history.
Market positioning
Frontier AI lab and infrastructure provider positioned at the intersection of generative AI and semiconductor manufacturing.
Geographic focus
Global, with primary operations in North America (Silicon Valley) and strategic focus on major semiconductor hubs in East Asia (Taiwan, South Korea).
Patents and IP
Founders hold foundational publications and prior IP related to 'Graph Placement Methodology' and 'AlphaChip' via Google and Stanford; new entity-specific patents are likely in filing stages.
About Anna Goldie
Anna Goldie is the Co-founder and CEO of Ricursive Intelligence. She was previously a Senior Staff Research Scientist at Google DeepMind, where she co-led the AlphaChip project, which utilized reinforcement learning to design four generations of Google's Tensor Processing Units (TPUs). Her work has been published in Nature and she was recognized as one of MIT Technology Review's 35 Innovators Under 35. She also served as a research scientist at Anthropic and holds a PhD in Computer Science from Stanford University.
Official website: https://ricursive.ai