The law does not care that it was an AI agent.
Your agents send emails, approve refunds, set prices and screen people. Aegis checks each action against the law in the moment before it happens, so unlawful ones never execute, and keeps the record that proves it.
Agents drift at the moment it matters most: when they decide and act.
Aegis stands in that moment as your last line of defense. It sits in the execution path, between your agent and the outside world, and nothing else about your setup changes.
Drag to compare. Same agent, same decision, different ending.
On its own, in milliseconds. This is the moment both sides of the slider share.
Nothing stands between the decision and the world. Mistakes arrive as complaints, claims and exam letters.
Allow, block, or hold for a human, against every law that applies to this action, this person, this country.
Written to your own storage as it happens, so the answer exists before anyone asks.
Companies just hired a new kind of worker. It acts on its own.
An AI agent sells, supports, screens and collects, around the clock, on your behalf. That is why you deployed it. It is also the problem.
Scale
One agent runs thousands of interactions a day. Emails, calls, screenings, approvals. No extra headcount.
Speed
Work that used to take a team now runs continuously, in software, at a cost per action close to nothing.
Autonomy
The agent decides and acts by itself, with no human in the moment. A mistake is not a bug ticket. It is a violation.
Five layers watch your agent. None of them watches the decision for unlawful risk.
Every control you already own operates either before the agent runs or after it has already acted. The moment that creates the liability sits between them.
Before it runs
- Model testing and red teaming
- SOC 2, ISO 42001, EU AI Act docs
- Policies and system prompts
- Guardrails and content filters
The decision
After it acted
- Monitoring and dashboards
- Incident review
- Every action captured in a log: the Ledger
A tribunal held Air Canada to a refund policy its own chatbot invented, rejecting the argument that the chatbot was a separate entity. The company that deploys the agent answers for what it does.
These are not future risks. They are today's penalties.
The same role. Three candidates. Three different duties.
Your screening agent scores candidates, and its score anchors the human decision that follows. The duties change with each candidate, and the agent cannot see any of them.
A human still makes the hiring decision. But the score anchors it, which is exactly why the law treats the scoring itself as the risk.
And not only what they send.
Three products, in the order most teams adopt them: check what agents say, guard what they do, keep the record that proves both.
Who this is for
Privacy first. We keep hashes, not your data.
A compliance layer that copied your data would be a new breach waiting to happen. Content passes through in memory, gets its answer, and is gone. What stays behind is proof that the check happened, never a copy of what was checked.
Aegis keeps
- hashes
- rule IDs and versions
- verdict codes
- counters and chain digests
- categorical telemetry
Aegis never holds
- message content
- prompts
- PII
- credentials or keys
- model reasoning
See where your agents are exposed.
Tell us what your agents do. We map them against the laws that apply, show you where the exposure sits, and price the case. No charge for the assessment.