Agentrys Secures $24.5M to Automate Semiconductor Design With AI Agents
The San Jose startup picked up backing from Etna Labs and MediaTek to build autonomous workflows for chip engineering teams.
Key highlights 路 2 min read
- Silicon Valley startup Agentrys has secured $24.5 million in total early-stage capital to bring autonomous AI agents into the complex, high-stakes world of semiconductor engineering.
- The financing package consists of a freshly closed $19.1 million seed round led by Etna Labs, following an earlier $5.4 million pre-seed tranche led by Taiwanese chipmaker MediaTek.
- Founded and led by chief executive Mark Ren, the San Jose-based company develops what it terms an Agentic Design Automation (ADA) platform.
The Scale ReportSilicon Valley startup Agentrys has secured $24.5 million in total early-stage capital to bring autonomous AI agents into the complex, high-stakes world of semiconductor engineering.
The financing package consists of a freshly closed $19.1 million seed round led by Etna Labs, following an earlier $5.4 million pre-seed tranche led by Taiwanese chipmaker MediaTek.
Founded and led by chief executive Mark Ren, the San Jose-based company develops what it terms an Agentic Design Automation (ADA) platform. The software functions as an open layer that allows hardware teams to build, deploy, and coordinate fleets of specialized AI agents designed to handle specific phases of silicon development, particularly chip verification and physical layout design.
Crucially, Agentrys is positioning its agent platform to plug directly into the established Electronic Design Automation (EDA) software suites that dominate the chipmaking ecosystem, rather than attempting to replace legacy toolchains outright.
Solving the Silicon Bottleneck
Designing advanced semiconductors has become one of the most resource-intensive disciplines in technology, characterized by multi-year timelines, soaring tapeout costs, and a chronic shortage of senior verification engineers. While generative AI has rapidly penetrated general software development, applying agentic models to hardware requires strict adherence to physical constraints and zero tolerance for hallucinated logic.
The fresh capital will go toward recruiting specialized AI researchers and engineers, refining the company's agent-native toolsets, and expanding enterprise pilot programs with commercial chipmakers.
Reporting based on coverage from @tradedvc on Instagram.
