At a glance
| Booth | Q6158 |
| Country | CA |
Company profile
Asterquanta Systems Inc is building an AI platform for analog semiconductor design around its Reinforcement Learning based Digital-Genie approach. The platform is intended to help semiconductor companies develop intellectual property faster, create richer design intelligence, and unlock new IP through AI-driven optimization and reusable engineering knowledge. Asterquanta Systems Inc supports AI adoption across analog semiconductor workflows through integration with existing tools, flexible deployment, and support for external AI agents. This integration model is designed so organizations can introduce AI incrementally without disrupting established design environments or replacing the tools already embedded in engineering workflows. The company also focuses on workforce development by upskilling semiconductor engineers, increasing productivity, and enabling teams to capture and reuse institutional knowledge. Its stated outcome is faster innovation, scalable AI adoption, and a workforce better equipped to develop the next generation of semiconductor products. Asterquanta Systems Inc is engaging with semiconductor companies, government programs, research institutions, and global innovation ecosystems, including Texas Instruments, GlobalFoundries, and India’s Ministry of Electronics and Information Technology.
Exhibits
The named platform is AQ Digital Genie, also presented as DGenie, and its technical approach combines reinforcement learning with large-scale design trajectory exploration. Digital-Genie applies AI-driven optimization to analog semiconductor design while retaining engineering knowledge so that useful design experience can be reused across later work. Teams can develop their own agents or deploy specialized capabilities for analog and mixed-signal circuit design, making the platform extensible to different engineering organizations. The supported engineering tasks include circuit design, verification, validation, optimization, and design-space exploration for analog and mixed-signal semiconductor work. Large-scale design trajectory exploration extends this workflow by allowing reinforcement-learning methods to evaluate broader paths through the design process rather than relying only on a single manual iteration sequence. The platform is designed to reduce development time and improve engineering productivity while helping teams capture institutional knowledge that would otherwise remain scattered across individual projects or engineers. Asterquanta Systems Inc also positions the technology to support faster and more reliable design convergence across semiconductor programs, connecting optimization work with verification and validation activities. Support for external AI agents allows organizations to connect specialized agent capabilities to the existing analog-design environment while keeping deployment flexible. Because the system is intended to integrate with existing tools, companies can apply AI to selected portions of the analog workflow first and expand usage as teams build experience. The overall offering therefore combines a reinforcement-learning design platform, reusable engineering knowledge, agent-based extensions, and design-space exploration for analog and mixed-signal semiconductor development.
Capabilities and products
- AI platform for analog semiconductor design
- AI-assisted analog and mixed-signal circuit design
- analog and mixed-signal circuit verification
- analog and mixed-signal circuit validation
- AI-driven circuit design optimization
- circuit design-space exploration
- support for external AI agents