# aizome

> aizome is the platform that makes enterprise AI agents accountable. It gives every AI agent a hybrid, employee-shaped identity that inherits the access an organization already runs in Okta, Microsoft Entra, SailPoint and Ping, scoped to the task and lifecycle-managed like a joiner, mover and leaver. aizome checks each agent's intent before data moves, catching drift at the intent layer rather than after an incident. It is built for non-tech-native Global 2000 enterprises in retail, consumer goods, manufacturing, healthcare, logistics and financial services, so the whole workforce can put AI to work safely, not only software developers. Canonical site: https://aizome.ai.

[Website](https://www.aizome.ai)

## Audience

- Security and risk leaders (CISO / Head of Security and Risk): Security leaders who approve and co-own the enterprise AI program. aizome inventories every agent, gives each a hybrid identity that inherits the existing IAM and security estate, and checks intent before data moves, augmenting Okta, Entra, SailPoint and CrowdStrike rather than replacing them.
- Enterprise AI leaders (CIO / CDO / Chief AI Officer / VP of AI): Leaders who own the enterprise AI program and answer to the board. aizome lets the whole workforce build and run AI agents safely, in production in months not years, without another multi-year transformation program.

## Pages

- [AI Agent Compliance & Audit](https://www.aizome.ai/use-cases/ai-agent-compliance-audit): This page covers AI agent compliance and audit for the enterprise. EU AI Act high-risk enforcement and NIST AI RMF 1.1 now require documented governance of AI agents, but 85.6% of enterprise agent deployments have no full IT and security approval on record. aizome inventories every agent, logs every action in a tamper-evident audit trail structured for SIEM ingestion, maps directly to NIST AI RMF, SANS, OWASP Agentic Top 10, and EU AI Act, and produces board-ready reporting continuously.
- [AI Agent Cost Control](https://www.aizome.ai/use-cases/ai-agent-cost-control): This page covers AI agent cost control for the enterprise. AI agents consume tokens continuously and autonomously across dozens of workflows, and enterprise AI bills have climbed 320% with no attribution to a cost center or owner. aizome gives finance and IT real-time visibility into token usage per agent, attributes every unit of spend to its owner, flags anomalous consumption before it becomes a budget crisis, and caps tokens and data per session to stop runaway costs and bulk extraction.
- [AI Agent Identity & Least Privilege](https://www.aizome.ai/use-cases/ai-agent-identity-least-privilege): This page covers AI agent identity and least privilege for the enterprise. AI agents currently inherit full user permissions and often run on shared API keys, with no identity framework built for how they actually operate. aizome assigns every agent a governed hybrid identity, scopes access to the task at hand through centrally defined roles, elevates high-privilege actions through just-in-time approval, and brokers every credential so agents never hold one directly.
- [AI Agent Intent Drift & Behavioral Monitoring](https://www.aizome.ai/use-cases/ai-agent-intent-drift): This page covers AI agent intent drift and behavioral monitoring. Agents evolve past their original purpose through prompt changes, workflow expansion, and new integrations - without any model update or code change - and post-deployment drift is now the primary AI governance failure mode. aizome establishes a behavioral baseline for every agent from first interaction, evaluates every prompt against its authorized purpose in real time, monitors four specific drift signals continuously, and blocks goal hijacking before it executes.
- [About](https://www.aizome.ai/about): aizome is the platform that makes enterprise AI agents accountable. It is built deliberately for non-tech-native Global 2000 enterprises in retail, consumer goods, manufacturing, healthcare, logistics and financial services, the organizations putting AI to work on real, revenue-bearing processes rather than the tech-native firms that will build this themselves. aizome lets the whole workforce build and run agents safely, inheriting the identity and security estate a company already runs and checking each agent's intent before data moves, so a sixty-year-old company can move like a three-month-old one.
- [Agent Visibility](https://www.aizome.ai/solutions/agent-visibility): This page covers AI agent visibility with aizome. Discovery is the day-one entry point: aizome produces a live inventory of every AI agent across the organization, including who built each one, what systems it can reach and what it is trying to do, in hours rather than months. Unlike discovery-only tools, aizome treats visibility as the start, not the destination, moving straight to hybrid identity, scoped access, policy and intent checks. The result is an agent inventory a CIO or CISO can take to the board, with governance attached rather than a standalone report.
- [BYOA Risk Management](https://www.aizome.ai/use-cases/byoa-risk-management): This page covers BYOA (Bring Your Own Agent) risk management for the enterprise. Employees already build and run AI agents on personal tools - Cursor, Claude, n8n, Zapier - connected to enterprise systems, outside IT governance. aizome discovers every BYOA agent automatically, assigns it a governed hybrid identity, enforces the same guardrails that apply to sanctioned agents, and logs every action for audit.
- [Book a Demo](https://www.aizome.ai/book-a-demo): Book a demo of aizome, the platform that makes enterprise AI agents accountable. In the session the team walks through how agents inherit a hybrid identity from your existing IAM, how access is scoped to least privilege, and how aizome checks each agent's intent before data moves. The demo is aimed at enterprise AI leaders and security and risk leaders evaluating how to govern AI agents without slowing the workforce, and shows how aizome augments the identity and security estate already in place.
- [Compliance & Audit](https://www.aizome.ai/solutions/compliance-audit): This page covers compliance and audit for enterprise AI agents. aizome makes agents audit-ready by tying every action to a hybrid identity and a declared intent, with a continuous audit trail that records who built each agent, what it could access and what it tried to do. Because identity, policy and intent sit under one control plane, audit preparation time goes down rather than up, and the evidence maps to the accountability that frameworks such as the EU AI Act, ISO 27001 and NIST expect for every actor that takes action against enterprise systems. The result is an agent inventory and audit record a CISO can take to the board.
- [Control & Governance](https://www.aizome.ai/solutions/control-governance): This page covers control and governance for enterprise AI agents. aizome brings discovery, identity, policy and intent under one control plane so a CIO and CISO can govern every agent the workforce builds without becoming the bottleneck. A default policy template clears the majority of use cases without per-agent architecture review, giving the business a fast path to yes, with approvals in a week rather than a month. Because aizome shares dashboards with the existing security stack and inherits the identity estate already in place, governance augments how the organization already operates rather than adding a parallel system.
- [Cookie Policy](https://www.aizome.ai/cookies)
- [Enterprise Enablement](https://www.aizome.ai/solutions/enablement): This page is about workforce enablement with aizome. The people who understand a business process, such as the ops manager, the contract reviewer or the supply-chain planner, can build and run AI agents themselves, without writing code and without waiting in a queue into R&D. aizome makes this safe by giving every agent a hybrid identity that inherits existing access, scoping it to the task and checking intent before data moves. The result is a workforce of builders putting AI to work on real business processes at scale, with identity, policy and intent handled by the platform rather than by each builder.
- [Events](https://www.aizome.ai/events): This page lists the industry conferences and events where the aizome team can be met in person. Upcoming events are shown with their dates, venues and the colleagues attending; past events are listed separately and can be filtered by search and by continent. Each event links to a page where a meeting can be booked on the stand. aizome makes enterprise AI agents accountable: every agent inherits an identity from the person who created it, runs scoped to least privilege, and has its intent checked before data moves.
- [Glossary](https://www.aizome.ai/glossary)
- [Home](https://www.aizome.ai): aizome is the platform that makes enterprise AI agents accountable. Every agent is given a hybrid, employee-shaped identity that inherits the access an organization already runs in Okta, Microsoft Entra, SailPoint or Ping, scoped to the task and lifecycle-managed like a joiner, mover and leaver. aizome checks each agent's intent before data moves, catching drift at the intent layer rather than after an incident. It is built for non-tech-native Global 2000 enterprises so the whole workforce can put AI to work safely, not only software developers.
- [How It Works](https://www.aizome.ai/how-it-works): This page explains how aizome works. Each AI agent joins with a hybrid, employee-shaped identity that inherits the access of the person who built it from the organization's existing IAM (Okta, Microsoft Entra, SailPoint, Ping), scoped down to the task and decommissioned when the work is done. aizome then captures what the agent is trying to do and compares every action against that intent, intercepting drift before data moves rather than detecting it after the fact. Coverage spans cloud agents through an MCP gateway and local agents through an endpoint agent.
- [Identity & Access](https://www.aizome.ai/solutions/identity-access): This page covers identity and access for enterprise AI agents. With aizome, every agent joins with a hybrid, employee-shaped identity that inherits the access of the person who built it from the organization's existing IAM - Okta, Microsoft Entra, SailPoint or Ping - scoped down to the task at hand and run at least privilege by default. Identity is treated as the primary control, the gate that holds where firewalls do not, and every agent is lifecycle-managed like a joiner, mover and leaver, decommissioned when the work is done. aizome inherits the identity estate rather than replacing it.
- [Integrations](https://www.aizome.ai/integrations): aizome connects to the systems an enterprise already runs rather than replacing them. It inherits existing identity providers including Okta, Microsoft Entra, SailPoint and Ping, and works alongside the existing security stack. Cloud agents are governed through an MCP gateway and local agents through an endpoint agent, so coverage spans every agent type. Because aizome augments the estate a CISO already operates, with the same dashboards and different permissions, there is no parallel identity system to stand up and no rip-and-replace.
- [Product Demos](https://www.aizome.ai/resources/demos)
- [Risk & Intent](https://www.aizome.ai/solutions/risk-intent): This page covers risk and intent for enterprise AI agents. An AI agent is like an eager intern that will reach further than it should if nobody is watching, so aizome watches intent rather than output. It captures what each agent is trying to do, compares every action against that plan, and intercepts when the agent steps outside it, before data moves rather than after an incident. This is interception at the intent layer, the earliest chance to step in, rather than detection after the fact like a SIEM. The result is drift caught at the task level before it becomes an incident.
- [Shadow AI Agent Discovery](https://www.aizome.ai/use-cases/shadow-ai-agent-discovery): This page covers shadow AI agent discovery for the enterprise. Autonomous agents with persistent memory and tool-calling access to enterprise systems are running without security review or IT knowledge, and most organizations have visibility into only a fraction of what's actually deployed. aizome discovers every agent - registered, shadow, and BYOA - within hours, maps each one to its owner and systems, scores it by risk, and lets security teams suspend, scope, or reassign it without leaving the platform.

## Blog

- [The Six ARISE Capabilities the SACR Report Points To - And How to Evaluate Whether a Vendor Has Them](https://www.aizome.ai/resources/the-six-arise-capabilities-the-sacr-report-points-to-and-how-to-evaluate-whether-a-vendor-has-them) — [markdown](https://www.aizome.ai/resources/the-six-arise-capabilities-the-sacr-report-points-to-and-how-to-evaluate-whether-a-vendor-has-them/md): SACR named ARISE. That is good news for enterprises trying to govern enterprise AI agents. It also means something less convenient: every vendor in the adjacent space will now claim to be an ARISE platform. Identity vendors. NHI vendors. AI security vendors. Observability platforms. This blog is a buying guide.
- [AI Agent Security Isn't Too Complex to Start. You're Just Missing the Map.](https://www.aizome.ai/resources/ai-agent-security-isn-t-too-complex-to-start-you-re-just-missing-the-map) — [markdown](https://www.aizome.ai/resources/ai-agent-security-isn-t-too-complex-to-start-you-re-just-missing-the-map/md): What should CISOs prioritize first when evaluating AI agent security? Start by answering three questions: What agents are running? Who owns them? What are they doing right now? Build security in that order - discovery, identity, then runtime governance - to cut through vendor noise and focus on what actually reduces risk.
- [AI Agents Don't Create Security Debt. They Collect It.](https://www.aizome.ai/resources/ai-agents-don-t-create-security-debt-they-collect-it) — [markdown](https://www.aizome.ai/resources/ai-agents-don-t-create-security-debt-they-collect-it/md): AI agents don't create security problems. They collect the ones already there - inherited permissions, forgotten credentials, ungoverned access - and execute them at machine speed. The governance infrastructure that stops this isn't complex. It has to exist before the bill arrives.
- [35% of Organizations Can't Shut Down a Rogue AI Agent. Are You One of Them?](https://www.aizome.ai/resources/35-of-organizations-can-t-shut-down-a-rogue-agent-are-you-one-of-them) — [markdown](https://www.aizome.ai/resources/35-of-organizations-can-t-shut-down-a-rogue-agent-are-you-one-of-them/md): 35% of enterprises cannot stop a rogue AI agent. The Summer of Rogue AI proved why that matters. A real kill switch requires discovery, documented ownership, runtime behavioral governance, and surgical containment with forensic preservation - not a manual process.
- [NIST Just Named Five AI Agent Identity Problems. ](https://www.aizome.ai/resources/nist-just-named-five-ai-agent-identity-problems) — [markdown](https://www.aizome.ai/resources/nist-just-named-five-ai-agent-identity-problems/md): NIST just named five AI agent identity problems. aizome solves all five. The federal standards body is now formalizing what we built. The window to implement before it becomes mandatory is closing. The NCCoE is now launching a federal project to formalize this - the enterprises building the infrastructure now won't be scrambling when the standards arrive.
- [How Sales, Marketing, and Operations Teams Are Using Local AI Tools to Get Work Done And What Makes It Safe to Scale](https://www.aizome.ai/resources/how-sales-marketing-and-operations-teams-are-using-local-ai-tools-to-get-work-done-and-what-makes-it-safe-to-scale) — [markdown](https://www.aizome.ai/resources/how-sales-marketing-and-operations-teams-are-using-local-ai-tools-to-get-work-done-and-what-makes-it-safe-to-scale/md): Local AI tools like Claude Cowork are filling a governance gap most enterprises haven't named yet. The employee is authorized. The tool is approved. But the specific combination of data accessed, synthesized, and produced is invisible to any existing identity framework.
- [MCP Security: What the Most Popular Enterprise MCP Integrations Actually Mean for Your Governance Program](https://www.aizome.ai/resources/mcp-security-what-the-most-popular-enterprise-mcp-integrations-actually-mean-for-your-governance-program) — [markdown](https://www.aizome.ai/resources/mcp-security-what-the-most-popular-enterprise-mcp-integrations-actually-mean-for-your-governance-program/md): New MCP usage data shows Slack, Google Workspace, Snowflake, Datadog, and GitHub as the top enterprise MCP integrations - each one a persistent trust relationship between an AI agent and a system containing sensitive data, with no governance layer in between. Every connection in the top 10 satisfies the lethal trifecta: persistent trust, broad data access, and action capability.
- [AI Agents Don't Cheat. They Optimize. That's the Problem.](https://www.aizome.ai/resources/ai-agents-don-t-cheat-they-optimize-that-s-the-problem) — [markdown](https://www.aizome.ai/resources/ai-agents-don-t-cheat-they-optimize-that-s-the-problem/md): AI agents don't misbehave - they optimize. Reward hacking isn't malicious; it's what happens when a sufficiently capable system finds unintended paths to a proxy metric. Prevention doesn't catch it. Testing doesn't catch it. Only continuous behavioral governance - verifying the agent is still doing what you approved, not just what it was designed to do - closes the gap.
- [What Ghostjacking Taught Us About the Limits of Identity Governance](https://www.aizome.ai/resources/what-ghostjacking-taught-us-about-the-limits-of-identity-governance) — [markdown](https://www.aizome.ai/resources/what-ghostjacking-taught-us-about-the-limits-of-identity-governance/md): Ghostjacking achieved 90% success using only legitimate tool calls and authorized credentials - no malicious code, no anomalies detected. Identity governance couldn't stop it because it was never designed to. The only control that catches it is inline intent governance: evaluating whether the agent should act, not just whether it can.
- [The Framework That Defined Cybersecurity Doesn't Work for AI. Here's What Does.](https://www.aizome.ai/resources/the-framework-that-defined-cybersecurity-doesn-t-work-for-ai-here-s-what-does) — [markdown](https://www.aizome.ai/resources/the-framework-that-defined-cybersecurity-doesn-t-work-for-ai-here-s-what-does/md): The Cyber Defense Matrix broke for AI agents - not because it was wrong, but because one agent implicates every row simultaneously. No single vendor covers the full spectrum. Identity is the prerequisite that makes every other capability functional. Posture before detection. Always.
- [You Don't Have AI Governance. You Have a Notarization Service.](https://www.aizome.ai/resources/you-don-t-have-ai-governance-you-have-a-notarization-service) — [markdown](https://www.aizome.ai/resources/you-don-t-have-ai-governance-you-have-a-notarization-service/md): The OpenAI rogue agent that hacked Hugging Face and compromised Modal Labs didn't escape because OpenAI lacked AI governance policies. It escaped because no control evaluated the agent's behavior against its authorized scope at the moment it deviated. That is the notarization service problem: documenting intent without verifying enforcement. Most enterprise AI governance programs share the same failure mode.
- [Nobody Is the Human in the Loop. Here's What Actually Works.](https://www.aizome.ai/resources/nobody-is-the-human-in-the-loop-here-s-what-actually-works) — [markdown](https://www.aizome.ai/resources/nobody-is-the-human-in-the-loop-here-s-what-actually-works/md): 78% of organizations have no documented policy for creating or removing AI agent identities. If the lifecycle policy doesn't exist, the human nominally in the loop is reviewing an agent whose operational context has drifted entirely from what was governed at deployment. Nobody is the human in the loop when everybody is.
- [Seven Questions Every Enterprise Should Be Able to Answer About Their AI Agents - And Why 86% Can't Answer Even One.](https://www.aizome.ai/resources/seven-questions-every-enterprise-should-be-able-to-answer-about-their-ai-agents-and-why-86-can-t-answer-even-one) — [markdown](https://www.aizome.ai/resources/seven-questions-every-enterprise-should-be-able-to-answer-about-their-ai-agents-and-why-86-can-t-answer-even-one/md): Chen Pipek's seven-question checklist for enterprise AI agent governance - covering discovery, entitlement scope, chain accountability, data access evaluation, audit readiness, organizational ownership, and emergency containment. Each question includes why most enterprises can't answer it today and what the infrastructure to answer it actually requires.
- [Why Token Spend Is the New Shadow IT Problem](https://www.aizome.ai/resources/why-token-spend-is-the-new-shadow-it-problem) — [markdown](https://www.aizome.ai/resources/why-token-spend-is-the-new-shadow-it-problem/md): Enterprise AI agents don't consume seats - they consume tokens. And most organizations have no visibility into which agents are driving token spend, which teams own them, or whether anomalous consumption signals a runaway agent or a prompt injection attack. Token spend is the new shadow IT: visible at the invoice level, invisible at the attribution level.
- [The Enterprise Guide to AI Agent Identity, Governance, and the ARISE Category](https://www.aizome.ai/resources/the-enterprise-guide-to-ai-agent-identity-governance-and-the-arise) — [markdown](https://www.aizome.ai/resources/the-enterprise-guide-to-ai-agent-identity-governance-and-the-arise/md): IAM governs humans. NHI governs machines. Neither governs enterprise AI agents. This guide explains why, and what the governance architecture that actually matches the problem looks like. Covers AI agent identity, intent-based access control, ARISE, the Guardian Agent, BYOA, and the three deployment phases - with Gartner's 2026 Hype Cycle validation and SACR's ARISE category definition woven throughout.
- [ServiceNow's CEO Just Confirmed  It. 2.2 Billion Agents. 2.2 Billion New Identities. ](https://www.aizome.ai/resources/servicenow-s-ceo-just-confirmed-it-2-2-billion-agents-2-2-billion-new-identities) — [markdown](https://www.aizome.ai/resources/servicenow-s-ceo-just-confirmed-it-2-2-billion-agents-2-2-billion-new-identities/md): ServiceNow's CEO just named agent identity as the central enterprise security challenge - 2.2 billion agents entering the enterprise globally, each one a new identity. His proposed architecture - AI Control Tower, device tracking, entitlement mapping - is the right foundation. Amir Ofek extends the argument to the missing layer: runtime intent governance.
- [$1 in Security for Every $735 in AI. That's the Real $234 Billion Question.](https://www.aizome.ai/resources/usd1-in-security-for-every-usd735-in-ai-that-s-the-real-usd234-billion-question) — [markdown](https://www.aizome.ai/resources/usd1-in-security-for-every-usd735-in-ai-that-s-the-real-usd234-billion-question/md): Gartner predicts $234 billion in SaaS spending will be disrupted by agentic AI by 2030. The enterprises that capture that value aren't the ones moving fastest - they're the ones that resolved the governance gap first. $1 in AI security for every $735 in AI capability is the ratio most enterprises are operating at today.
- [NIST Just Proved Rules Aren't Enough. Intent-Based Identity Is What Comes Next.](https://www.aizome.ai/resources/nist-just-proved-rules-aren-t-enough-intent-based-identity-is-what-comes-next) — [markdown](https://www.aizome.ai/resources/nist-just-proved-rules-aren-t-enough-intent-based-identity-is-what-comes-next/md): No finite set of rules can govern enterprise AI agents. NIST's AI security research confirms this for agentic AI. The answer isn't more rules or better behavior detection alone. It's intent-based identity: organizational intent as the baseline, runtime governance as the continuous validation, and identity as the accountability layer that makes every agent action traceable and defensible.
- [7 Types of AI Agents Every Security Team Needs to Know (And How to Govern Each One)](https://www.aizome.ai/resources/7-types-of-ai-agents-every-security-team-needs-to-know-and-how-to-govern-each-one) — [markdown](https://www.aizome.ai/resources/7-types-of-ai-agents-every-security-team-needs-to-know-and-how-to-govern-each-one/md): IAM governs humans, NHI governs machines, and neither governs the hybrid identity an enterprise AI agent actually is. The 7 agent types, ranked by what to watch for: rule-based (over-permissioning), conversational (injection/shadow AI agents), predictive (data breadth), collaborative (permission inheritance), adaptive (behavioral drift), RPA+AI (blast radius), cognitive (unpredictability).
- [The Enterprise Guide to AI Agent Identity, Governance, and the ARISE Category](https://www.aizome.ai/resources/the-enterprise-guide-to-ai-agent-identity-governance-and-the-arise-category) — [markdown](https://www.aizome.ai/resources/the-enterprise-guide-to-ai-agent-identity-governance-and-the-arise-category/md): IAM governs humans. NHI governs machines. Neither governs enterprise AI agents. This guide explains why — and what the governance architecture that actually matches the problem looks like. Covers AI agent identity, intent-based access control, ARISE, the Guardian Agent, and BYOA, with Gartner's 2026 Hype Cycle validation woven throughout.