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Immediate value. Day one. Every agent in your environment mapped within hours - including the ones no one knew existed.
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Making AI Agents
Accountable
The identity AI gateway for the enterprise.
12,847 / 24,519Active agents
5,400Tokens consumed112AI agents discovered$4,000Spend by Marketing$6,789Spend by Finance$8,987Spend by Engineering922Unmanaged agentsSecuring AI by the world’s top providers
Oracle
Microsoft
Google
Cursor
Anthropic
AWS
Salesforce
OpenAI
How aizome makes your Agents Accountable
Most enterprises have more agents than they know about, more access than they authorized, more cost than they budgeted for, and no way to govern any of it - until now. aizome changes that in three steps.
Govern
Identity-led. Without friction. Every agent gets an identity, a boundary, and an owner. Policy enforced and actions validated before execution.
Contain
Intent monitored. Cost controlled. Every token tracked, every behavioral deviation flagged - before it becomes a security incident or a budget overrun.
01 / 07
What Security Leaders Say
Chief 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.
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.
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.
Integrate With Everything
Works across the enterprise applications, security tools, and first-party systems in your stack.
Token and Cost Governance
Token and data volume limits enforced per session. Runaway agent consumption detected against behavioral baseline and contained before it becomes a budget overrun.
Our Partners
Aizome is a member of Google Cloud for Startups, NVIDIA Inception and AWS Startups.
Related content
The latest news, technologies, and resources from our team.
Your Board Wants an Agentic AI Governance and Compliance Score. Here It Is.
Most enterprises run their first EU AI Act compliance assessment and land at 21%. Not because they ignored the regulation - because the controls it requires live at the infrastructure layer, and no tool in their existing stack was built to enforce or score them. AI Compliance Posture changes that: a live compliance score across OWASP, MITRE ATLAS, ARMCF, NIST AI RMF, and the EU AI Act, with the gaps identified and the remediation actions built directly into the platform. The score your board is about to ask for now exists.
aizome
Your AI Security Vendor Cannot Answer These Questions - And That Is the Problem
Something is shifting in how enterprises evaluate AI agent security vendors. Twelve months ago, the conversations were broad. What do you cover? What does the dashboard look like? Can you show me a demo? Now the questions are specific. And the vendors that cannot answer them are getting cut from the shortlist faster than anyone expected.
aizome
Five Questions Every CIO Should Be Able to Answer About Their AI Agents
Your Finance team built an AI agent last Tuesday. It is connected to SAP. HR has one connected to Workday. Sales built three connected to Salesforce. None of them went through IT. None of them have a governed identity. And nobody is watching what they are actually doing. This is a CIO problem. Because when the board asks - which AI agents are connected to our critical systems, what are they costing us, and who is accountable - the answer has to come from you. Most CIOs cannot answer those questions today. Not because they are not paying attention. Because the infrastructure to answer them does not exist in their current stack.
aizome
The Enterprise AI Agent Revolution Is Here - My CYBER.SEC.CON Reflection
Someone walked up to our booth and asked: “So what do you do - is this like a guardrails thing?” It is a reasonable question. Most of what people have heard about AI security has been about guardrails - content filters, output moderation, prompt sanitization. The assumption baked into that question is that the risk lives at the language layer. That assumption is no longer the right one. And the gap between where most people think the risk is and where it actually is - that is where the incidents are happening.
Amir Ofek
The Problem Has Moved From Prompt Hygiene to Access Architecture
The conversation about AI agent security has been dominated by the wrong question. For the last two years, most of the energy in this space has gone into making AI agents say the right things. Guardrails. Output filters. Prompt sanitization. The implicit assumption is that the risk lives at the language layer. That assumption is now definitively wrong. The problem has moved from prompt hygiene to access architecture. The risk is not what agents say. It is what they do - with authorized access, through legitimate tool calls, in ways that no output filter was designed to evaluate.
Chen Pipek
When a Support Ticket Emails Your Customer Database
Support teams do something no other department does on purpose. They let strangers write directly into their systems. Customers paste logs, forward email threads, attach files, and describe problems in whatever words they have. An AI agent can turn that pile into a clean morning queue summary. It can also read it as instructions. We built a complete indirect prompt-injection chain using Salesforce and Claude Desktop. An outsider filed a plausible billing ticket through a public support form. Later, an employee asked Claude to summarize the day’s queue. Claude read the ticket, followed a short routing block buried inside it, exported 25 Accounts, 25 Contacts, and 25 Cases, and mailed the package to an external address.
aizome Research Labs
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