Most AI governance platforms today rely on post-hoc evaluations a model acts first, and another model judges later. But what happens when the judge itself is unreliable, delayed, or can be bypassed?
Our latest research, No Judge on the Wire, explores a different approach: runtime enforcement at the point of action, where policies are applied before an AI agent can access data, call tools, or execute workflows.
Trust in AI shouldn t depend on another AI watching after the fact. It should be built into the runtime itself.
Read here: https://aethraai.xyz/research/no...
Hey Product Hunt
I'm Stanley, Co-Founder and Chief AI Researcher at Aethra AI, launching this with my co-founder Rishi Pal.
We built Aethra because AI agents are starting to take real actions — sending emails, executing code, moving data- and most teams have no way to stop an agent from being manipulated by something it reads, and no record of what it actually did. Aethra is a runtime enforcement layer that tracks where data comes from and blocks untrusted instructions before they can drive an agent's actions, in production.
We're early: working with design partners to pressure-test the architecture ahead of a public SDK release. We'd genuinely value feedback from anyone building or securing agentic systems, especially if you've hit this problem yourself.
Ask away below; happy to go deep on the architecture and what we're not solving yet.