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Picture this: your engineering team just deployed a fleet of AI agents built on LangChain. They’re handling customer queries, updating tickets, and pulling data from half a dozen APIs. Then someone asks the awkward question, “Wait, what credentials are those agents using?” A long silence follows. You’re not alone.
Seventy-nine percent of organizations lack written policies for governing AI agents but have already pushed them into production, according to a 2025 EMA survey, conducted jointly with Ory, of 271 IT, security, and IAM professionals across the US, UK, Canada, France, and Germany.
According to the same EMA survey, 60.5% are cramming autonomous agents into hybrid human/service account models built for an era when “non-human” meant a cron job, not an LLM with tool access and decision-making latitude.
The numbers get worse under scrutiny. A CSA Research Note published in 2026 found that 68% of organizations can’t distinguish agent actions from human activity, 74% admit agents routinely get more access than they need, and 43% rely on shared or generic service accounts.
Only 36% have established dedicated agent identities with distinct permission sets. That’s a compliance nightmare waiting to happen, and an auditor’s dream.
If you’re building agents on LangChain, CrewAI, or custom runtimes, you need an identity layer that doesn’t care which orchestration framework you picked.
CSA readers know the checklist:
Here are seven platforms that deliver exactly that; no framework lock-in required.
We focused on one scenario: teams deploying AI agents on LangChain, CrewAI, or custom runtimes who need non-human identity management without coupling to any single framework. Each platform was scored against five criteria:
Our rankings incorporate practitioner sentiment and documented real-world usage alongside these technical criteria.
Ory takes a fundamentally different approach to IAM. Instead of a monolithic black box, it’s built as a set of highly engineered, modular, API-first components: Ory Hydra for OAuth and OIDC, Ory Kratos for identity management, Ory Keto for Zanzibar-style fine-grained permissions, and Ory Oathkeeper as the access proxy, all released under the permissive Apache-2.0 license.
This isn’t theoretical architecture. It already runs at ChatGPT’s scale, managing identity for 1.2 billion weekly users after OpenAI adopted an Ory Enterprise License when traditional ‘black-box’ CIAM architectures couldn’t meet their requirements for structural control, innovation, scalability, and self-hosting.
Benjamin Billings, Engineering Manager at OpenAI, put it plainly: ‘OpenAI wanted a partner that could help enable our vision for owning our identity processes, data, and success. We have a lot of partners, and Ory is one of our best.’
Now Ory is bringing that same architecture to agentic AI with MCP OAuth 2.1, machine-scale token issuance, and Zanzibar-style authorization, backed by full self-managed deployment flexibility (on-premises or private cloud) to enforce strict security policies directly at the point of agent execution.
Best for: Teams that want highly engineered, modular, API-first IAM with serious fine-grained authorization, complete deployment control, and the capability to enforce strict security policies at the exact moment an agent performs an action.
Less ideal if you require a completely no-code SaaS with zero operational overhead, though Ory Network significantly narrows that gap.
Descope’s Agentic Identity Hub 2.5, released in June 2026, tackles agent identity from the opposite direction: low-code and purpose-built.
The platform now supports autonomous agents with no delegating human user, CIBA-based step-up authentication for human-in-the-loop approvals, and standalone MCP auth that doesn’t disrupt your existing user authentication layer.
It’s already powering authentication for hundreds of MCP servers and millions of agentic transactions.
Best for teams prioritizing rapid implementation with minimal coding, especially for MCP-centric agent deployments.
Less ideal if you need deep self-hosting flexibility or fine-grained, composable authorization beyond its built-in policy controls. Descope’s low-code approach trades customization depth for speed.
Aembit takes a workload-first approach, building IAM specifically for non-human identities and agentic AI. Its platform provides secretless, just-in-time, policy-based access driven by continuous workload attestation.
Instead of static credentials, access is brokered at runtime based on verified workload attributes: what the workload is, where it’s running, and what it’s supposed to be doing.
Best for enterprises running poly-cloud and on-premises workloads that need strong workload attestation and a bridge between human and agent identity contexts.
Less ideal if you need a full CIAM solution for end-user login or extensive policy authoring, Aembit focuses squarely on the workload side of the equation.
Auth0 (Okta) extended its established CIAM platform with “Auth0 for AI Agents,” which reached General Availability in November 2025.
The suite brings a mature identity backbone to the agent problem, with Token Vault for centralized OAuth token storage, CIBA-based Asynchronous Authorization for human-in-the-loop, fine-grained authorization for RAG (retrieval-augmented generation), and User Authentication.
MCP Auth remains in Early Access, and SDKs are available for LangChain, LlamaIndex, and Vercel AI SDK.
Best for teams already invested in the Okta ecosystem who want rapid integration with popular agent SDKs and a mature CIAM foundation.
Less ideal if you need full self-hosting or are cost-sensitive at high agent volumes, and remember MCP auth is still in Early Access, so it may not yet cover every production edge case.
WorkOS approaches agent identity from the developer-first B2B auth angle. Its MCP Auth, launched in 2025, acts as a spec-compliant OAuth 2.1 authorization server for MCP servers, supporting per-agent M2M Client Credentials, PKCE, RBAC, fine-grained permissions, SSO, SCIM, and audit logging.
They also published auth.md, an open protocol for agent service-root discovery of OAuth Protected Resource Metadata, a practical contribution to making agents discover auth endpoints without hardcoding them.
Best for SaaS companies adding enterprise identity to their products while needing a clean, standards-based path to authenticate AI agents.
Less ideal if your use case extends beyond B2B SaaS into multi-cloud workload attestation or complex agentic authorization policies. WorkOS shines on the auth layer but doesn’t offer the depth of a dedicated workload IAM or fine-grained permissions engine.
SPIFFE (Secure Production Identity Framework for Everyone) and its reference implementation SPIRE are CNCF-graduated projects that solve a foundational problem: how do you give every workload, including AI agents, a cryptographically attested identity without static secrets?
SPIRE issues short-lived SVIDs (SPIFFE Verifiable Identity Documents) based on runtime environment attributes, not passwords or API keys that someone copied into a config file.
Best for cloud-native teams that need a foundational workload identity layer and are comfortable combining it with a separate authorization engine.
Less ideal if you expect a turnkey IAM with credential brokering, human identity, or policy authoring. SPIFFE/SPIRE is the identity issuance layer, not a complete solution.
Keycloak is the Red Hat-backed open-source IAM that many enterprises already know. It supports SSO, SAML, OAuth 2.0, OIDC, user federation, fine-grained authorization, and MFA out of the box.
While not purpose-built for AI agents, its machine-to-machine Client Credentials flow can be configured for agent identities, and if your organization already runs Red Hat or Java-heavy infrastructure, it’s the path of least resistance.
Best for organizations already running Red Hat or Java stacks that want to reuse existing identity infrastructure for agent auth without introducing a new platform.
Less ideal if you need a modern developer experience, cloud-native scalability at the level of dedicated agent identity platforms, or specialized AI agent governance features. Keycloak will need custom extensions to match purpose-built alternatives on agent-specific governance.
Let’s be honest about where we are. According to the same 2025 EMA survey cited earlier, 52.8% of organizations want an all-in-one IAM platform for agentic AI, but only 24% have achieved it. The rest are stitching together best-of-breed components that weren’t designed to talk to each other.
Self-hosting flexibility sounds great until you’re the one managing SPIRE at 3 AM. Open source brings freedom, but it also brings operational overhead that many teams underestimate.
Even the best runtime access control can’t stop shadow agent proliferation, developers spinning up agents with shared API keys and no governance. The CSA Agent Identity Governance Framework defines five distinct agent identity types: Copilot, Autonomous Agent, Orchestrator, Ephemeral Sub-Agent, and Agent-as-a-Service.
Each requires different credential lifecycles and monitoring obligations. Very few platforms model all five natively.
Moreover, the same EMA survey pointed out that cost is another wildcard, as 47% of organizations worry about rising or unpredictable IAM costs. SaaS pricing that looks reasonable at ten agents can become eye-watering at ten thousand, while self-hosted brings its own infrastructure and staffing costs.
There’s no universally right answer here, only what fits your scale, budget, and engineering capacity.
According to the CSA research note cited earlier, 47% of enterprises experienced a confirmed AI-agent security incident in the 2025–2026 window, and 58% took five hours or longer to detect it.
The NHI population explosion: 45 non-human identities for every human on average, according to a white paper by the Cloud Security Alliance titled “The Non-Human Identity Governance Vacuum.” In cloud-native settings, that disparity widens to a ratio of 144-to-1. This structural exposure is compounded by an 81% year-over-year increase in AI-related secrets to more than 1.27 million exposures.
28.65 million hardcoded secrets were added to public GitHub repositories in 2025 alone, a 34% year-over-year increase. It’s clear that static credentials are still everywhere, and they are the weakest link.
The IAM landscape for AI agents is maturing fast, but one principle already stands out: decouple identity from your agent framework, or you’ll regret the lock-in later. Ory leads in modular API-first design and machine-scale token issuance, deploying its highly engineered identity architecture that handles OpenAI’s 1.2 billion weekly active users.
Descope and Aembit shine in purpose-built agent features for teams that want to move fast. Auth0 and WorkOS offer strong CIAM-to-agent bridges for organizations with existing investments. And SPIFFE/SPIRE and Keycloak provide open-source foundations for teams with the engineering muscle to customize.
Choose based on your tolerance for engineering investment, self-hosting requirements, and how deep your authorization needs go. Pair any choice with a solid governance framework because technology alone won’t close the IAM readiness gap when 79% of organizations have already deployed agents without written policies.
The window to fix this is now, and it won’t stay open forever.
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