Opaque just raised $24M in Series B funding at a $300M valuation, and if you work anywhere near sensitive data, you should probably sit up a little straighter. This is not another artificial intelligence company promising magic dust and hockey sticks. This is Opaque Systems, built out of UC Berkeley’s RISELab, where Ion Stoica, Raluca Ada Popa, Rishabh Poddar, Wenting Zheng, and Chester Leung turned academic muscle into enterprise armor. These are not tourists in security. They wrote the textbooks, then decided to commercialize the footnotes.
Walden Catalyst Ventures led the round again, with Intel Capital, Race Capital, Storm Ventures, and Thomvest Ventures returning to the table, plus strategic backing from ATRC. When deep tech investors keep doubling down, it usually means one thing. The tech works. And the market pain is real.
Aaron Fulkerson is now CEO, stepping in with operator chops, while co-founder Rishabh Poddar moved into the CTO seat. Raluca Ada Popa continues as President and co-founder. Ion Stoica remains a gravitational force behind the company. This is what grown-up scaling looks like. Founder DNA intact. Professional horsepower layered on top.
What does Opaque actually do? They make confidential AI possible. Not marketing-confidential. Cryptographically enforced, hardware-backed, mathematically provable confidential. Their platform lets enterprises run analytics and AI on sensitive data using secure enclaves so the data stays protected even while it is being processed. Finance. Healthcare. Insurance. The industries where a data leak is not a headline, it is a crater.
The origin story matters. Opaque commercializes MC², a Berkeley-born open-source project focused on secure multi-party collaboration. Translation: multiple organizations can compute on shared insights without exposing their raw data. In a world obsessed with AI, the real bottleneck is not model size. It is trust. Opaque is building the infrastructure layer where trust is engineered, not assumed.
Seed was $9.5M. Series A was $22M. Now another $24M. Roughly $55.5M total to push confidential computing from research paper to revenue engine. That kind of capital stack says the bet is long-term. Infrastructure plays always are.
The takeaway for founders is simple. If you are solving a problem that regulators, CISOs, and boards lose sleep over, and you can prove it with real science, capital will find you. The takeaway for enterprises is even simpler. AI without security is a liability wearing a hoodie.
