Trust infrastructure for AI agents

The agent decides.
The envelope enforces.

Envellum sits between your AI agents and the systems they touch. Allowed actions pass through. Nothing else does.

01 / The shift

AI agents went from chat to action.

They read databases, write to ledgers, and call APIs on production systems. The security model that worked for chat assumed the language model would follow its instructions. It does not, reliably.

Privilege escalation Authorization bypass Scope violation Data exfiltration

The same handful of failure classes keep showing up. Patches fix bugs one at a time as they are identified. New bugs in the same class keep coming back.

02 / Today's defenses

Today's approaches all share one property: hope.

The system prompt

Hopes the agent follows it.

The watcher model

Hopes to catch a bad call before it lands.

The output filter

Hopes to match the right strings.

"We told it not to" is not an answer.
03 / A different layer

Envellum is not another guardrail.

The envelope sits between your agent and everything it touches. The decision does not depend on what the agent says, or on what a watcher model thinks it sees.

What is allowed is defined explicitly:

tools scopes data flows

Anything else is denied at the boundary, before it executes.

The agent reasons.
The envelope enforces.
04 / What the envelope holds

Configured for your environment, the envelope holds rules like:

CASE 01

Your agent cannot read another customer's data.

CASE 02

Your agent cannot escalate its own permissions.

CASE 03

Your agent cannot call a tool you have not approved.

CASE 04

Your agent cannot tamper with the audit log.

05 / Built for regulated industries

Where boundaries are not optional.

Healthcare

For agents that handle protected health data, where access flows have to hold up under audit.

HIPAA

Financial services

For agents that read customer accounts, where the controls have to hold up under external audit.

SOX PCI‑DSS

Government and enterprise

For agents under strict access controls, where every decision needs a record.

FedRAMP EU AI Act SOC 2
06 / Why now

The threat model has changed.

Agents are being deployed faster than the security model is catching up. Adversaries have new tools too. Defenses built for slow attackers do not hold against attackers that aren't.

The boundary needs to.

Stay in touch.

If you are building agents, securing them, or thinking about the same problem, drop us a note.