Stop choosing between LLM intelligence and PII compliance

Choosing non-sovereign LLM inference should NOT equal the shortening of PII compliance in 2026. Considering the latest leaks, hacks, and severe security compromises of even top-tier AI behemoths, the obvious elephant in the room is even more apparent, reminding us that data leakage is the number one barrier to pragmatic enterprise AI adoption, that is beyond fancy chatbots that farm media headlines as a KPI. Sending raw prompts to the cloud is not only a risk of private employee data leaving your premises, but a risk that subjects the profitability and even the vitality of an entire business model. At the same time, building basic custom filters on 70B parameter models is an unjustifiable cost, to say the least, if not straight-up absurd. For that, we’re releasing F1 Mask, our first open weights model in the new ARPA Micro series. We're looking at a tiny 270M parameter middleware agent designed to act as a local privacy firewall. Built on the pop Function Gemma 3 base, it identifies an