Making AI Agents
Accountable

Identity and control for every AI agent in your enterprise

12,847 / 24,519Active agents

How aizome makes your Agents Accountable

Most enterprises have more agents than they know about, more access than they authorized, and no way to govern either. aizome changes that in three steps.

Illustration of discovering all AI agents across the enterprise

Discover

Immediate value. Day one. Every agent in your environment mapped within hours - including the ones no one knew existed.

Illustration of assessing and scoring risk across AI agents

Assess Risk

Prioritize what matters most. Every agent risk-scored by what it accesses, what it does, and whether it is behaving as intended.

Illustration of controlling and governing AI agents through identity and intent

Control and Govern

Identity-led. Without friction. Policy and identity enforced automatically at every layer. Actions validated before execution.

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What Security Leaders Say

Arnab Bose
AsanaChief Product Officer, Asana (former CPO, Okta)

Arnab Bose

"The governance challenge around enterprise AI agents is real, and it won't be solved by extending existing IAM frameworks. aizome is tackling it the right way."

One Platform, End to End

Firewalls won't work. An agent knocks on their door a thousand times an hour until it finds the gap. Identity is the only gate that holds: the one your enterprise has spent two decades building.

Govern Identity

Agents inherit the identity of their user, scoped to the task at hand, lifecycle-managed, and decommissioned when the work is done.

Illustration of governing AI agent identity, scoping, and permissions

Intercept Intent

Agents will reach further than they should if nobody is watching. So we watch the intent, not the output: what the agent is trying to do, and why. The earliest chance to step in.

Illustration of intercepting and validating AI agent intent before execution

Built For Enterprise Agents

Ship-to-bill. Talent reviews. Contract monitoring. Customer-care triage. The unglamorous, revenue-impacting, buried-in-the-middle-of-the-business processes. The work nobody shouts about but no organization could live without.

Illustration of enterprise-scale AI agent governance architecture

Integrate With Everything

Works across the enterprise applications, security tools, and first-party systems in your stack.

Illustration of aizome integrating with existing enterprise security and identity tools

Our Partners

Aizome is a member of Google Cloud for Startups, NVIDIA Inception and AWS Startups.

Google Cloud for Startups
NVIDIA Inception Program
AWS Startups

Related content

The latest news, technologies, and resources from our team.

  • You Don't Have AI Governance. You Have a Notarization Service.

    Most enterprise AI governance programs are notarization services. They witness the policy. They do not verify the control. A notarization does not verify the underlying facts - it witnesses the signature. The OpenAI incident illustrates what happens when an agent operates without governance that verifies controls - not just documents them.

    Amir Ofek

    Amir Ofek

  • Nobody Is the Human in the Loop. Here's What Actually Works.

    Human-in-the-loop governance is the most widely cited answer to the enterprise AI agent risk problem. It is also the answer that fails most reliably in production. Not because the concept is wrong. The instinct to keep a human accountable for consequential AI actions is correct. The problem is that "human-in-the-loop" as an implementation strategy breaks down in three distinct ways before most enterprises realize it has broken - and the replacement architecture is rarely in place when it does.

    Chen Pipek

    Chen Pipek

  • Seven Questions Every Enterprise Should Be Able to Answer About Their AI Agents - And Why 86% Can't Answer Even One.

    The 2026 CISO AI Risk Report surveyed 235 large-enterprise security leaders and found that 86% do not enforce access policies for AI identities. Not 86% who haven't gotten around to it yet. 86% who have thought about it, assessed their infrastructure, and found that enforcing access policies for AI agents is something their current stack cannot do. These are the seven questions they cannot answer. None of them are advanced. All of them are baseline.

    Chen Pipek

    Chen Pipek

  • Why Token Spend Is the New Shadow IT Problem

    A decade ago, the shadow IT problem looked like this: employees signing up for SaaS tools with a credit card, bypassing procurement, running business workflows on software IT didn't know existed. The same problem is back. It looks different this time. And almost no organization has solved it. Token spend is the new shadow IT.

    aizome

  • The Enterprise Guide to AI Agent Identity, Governance, and the ARISE Category

    Enterprise AI agents are no longer a future technology. They are operating in Finance, HR, Sales, Operations, and IT at organizations across every industry, accessing sensitive data, executing multi-step workflows, and making consequential decisions, often with no human in the loop. The identity and governance infrastructure designed to secure human employees and traditional machine identities was not built for this.

    aizome

  • ServiceNow's CEO Just Confirmed It. 2.2 Billion Agents. 2.2 Billion New Identities.

    On ServiceNow's latest earnings call, Bill McDermott said something that stopped me. "There are 2.2 billion agents entering the enterprise globally. That's 2.2 billion new identities." That is the most important statement made about enterprise AI security on an earnings call this year. When a Fortune 500 CEO names agent identity as the central enterprise security challenge, in front of investors, on a quarterly earnings call, the category has officially arrived.

    Amir Ofek, aizome

    Amir Ofek


Questions, Answered

The things enterprise teams ask us first. Talk to us

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