Ariovis

AI and automation

Secure AI agents

Give AI agents autonomy without losing control over their identities, their tools, their data and what they actually do.

An agent is neither one more user nor just another API. It decides, calls tools and produces real effects in your systems. The question is no longer only “who signs in”, but “which action may run, under which mandate, on which data”.

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Does this sound familiar?

  • Teams are already connecting agents to internal APIs and data.
  • Agents rely on tokens, secrets or service accounts that nobody really governs.
  • No one has a precise picture of the tools or MCP servers in use.
  • Authorization rules are hard-coded inside the agents or the applications.
  • Teams can filter prompts, but cannot contain an action at runtime.
  • The SOC lacks the context to tell drift, prompt injection and compromise apart.

What you are trying to achieve

  • Give every agent an owner, an identity and an explicit mandate.
  • Limit the secrets, privileges and tools it can reach.
  • Decide dynamically which actions are allowed.
  • Protect prompts, MCP servers, APIs, RAG sources, memory and workloads.
  • Detect an agent exploring or acting outside its scope.
  • Contain, revoke and explain an incident.

The Ariovis capabilities involved

Each offer keeps its own role. Here is exactly what it brings to this situation.

  • AI agent protection

    See what the agent actually does, understand its blast radius and contain its effects at runtime.

    See the offer

  • Fine-grained authorization

    Decide whether a specific action may run, based on identity, resource and context, outside the agent's own code.

    See the offer

  • Privileged access and secrets

    Take secrets out of prompts and configuration files, and cut the privileges the agent holds permanently.

    See the offer

  • IAM strategy and Zero Trust

    Set the entry rules: who may deploy an agent, under which mandate and which operating conditions.

    See the offer

  • Trapster — Deceptive Security

    Place credible decoys that reveal an agent exploring beyond what it was entrusted with.

    See the offer

AI agent protection does not replace IAM. It extends it to the agent's tools, decisions and real-world effects.

Where to start

Pick one agent, one business workflow, its tools and its data, then map its real blast radius.

  1. 01Choose one agent already in use or about to ship, on an identifiable business workflow.
  2. 02List its tools, MCP servers, APIs, data sources and memory stores.
  3. 03Identify the identity, secrets and privileges it uses today.
  4. 04Describe the actions it can trigger, and those that should be refused.

A Practical Starting Point

A short format, already online, to get an objective view of your situation before committing to a project.

  • Runtime

    A useful starting point to situate your maturity on dynamic authorization for AI usage (MCP, RAG, ABAC/PBAC).

    Runtime

  • Fine-grained Authorization

    Helps qualify the applications and APIs your agents will call before opening any access.

    Fine-grained Authorization

Explore the Topic

Our published content that speaks directly to this situation.

Understand the Concepts

The notions worth sharing with your teams on this topic.

Does this use case look like yours?

Tell us about your context. Together we identify the priority capabilities and the first useful step.

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