Aembit
Identity control plane that brokers short-lived, policy-scoped credentials for AI agents, MCP servers, and non-human workloads.
The audit trail is where identity vendors get caught, and it's where Aembit is strongest: Blended Identity logs which agent acted and on whose behalf, so you stop reading "the user did it" in logs for actions a spawned agent took. Add the MCP Identity Gateway with tool filtering and the one-click kill switch and you have the three controls a security team actually asks for before an agent touches production data. At $20 per agent per month on the Teams tier it's reasonable for a team running ten agents. It is not a secrets store — if that's what you need, HashiCorp Vault is the better fit and Aembit works alongside it. Skip it if three static service accounts are your whole non-human estate.
Verified 3d ago · liveness 73/100 · cite: rightaichoice.com/tools/aembit
- Security and platform teams putting AI agents into production with per-agent policy and audit
- Regulated organizations that must prove which actions were agent-initiated vs. human-initiated
- Enterprises securing employee-connected personal agents like ChatGPT, Claude, and Meta Muse
- Teams standardizing MCP server access through a policy-enforcing gateway with tool filtering
- Companies with only a few static service accounts and no agent traffic
- Open-source-first shops committed to assembling SPIFFE plus a secrets manager in-house
- Buyers who want a general-purpose secrets store rather than an agent identity control plane
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Skip Aembit if your entire non-human estate is a handful of static service accounts with no agent traffic — you'd be paying per-agent for an audit attribution problem you don't have yet.
Exceeding the free Starter limits doesn't stop you — Aembit automatically moves you into a free trial of the Enterprise plan, so watch for that trial ending if you've quietly added more agents or workloads.
Priced for a single team: $20/agent/mo on Agentic AI Teams and $20/workload/mo on Workloads Teams, both of which you get to try free at 3 agents / 10 workloads. That lands between free open-source SPIFFE-and-vault assembly (cheap in license, expensive in engineer weeks) and enterprise non-human IAM suites sold on annual contracts. At 500 agents the per-unit model stops being obviously cheapest — that's the Enterprise conversation.
In short
Aembit — Identity control plane that brokers short-lived, policy-scoped credentials for AI agents, MCP servers, and non-human workloads. Best for Security and platform teams putting AI agents into production with per-agent policy and audit, Regulated organizations that must prove which actions were agent-initiated vs. human-initiated, Enterprises securing employee-connected personal agents like ChatGPT, Claude, and Meta Muse. Free to start; paid plans from $20/mo.
No head-to-head comparison for Aembit yet — the alternatives below are the closest matches we list.
What's new in Aembit
Checked 3 days agoAcross the latest 1 update: 1 news mention.
What people actually say about Aembit — is it worth it?
We scanned public community sources for Aembit on Oct 14, 2026 and could not establish that the discussion we found is about this tool rather than something else sharing its name. Only 2 of the posts we fetched could be positively tied to Aembit. Rather than publish a sentiment score built on the wrong subject, we publish nothing here and re-run the scan.
Viability Score
How well maintained and how widely used is Aembit? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this
Last calculated: October 2026
How we score →Key Features
- Secretless authentication for AI agents, MCP servers, and workloads
- Policy-scoped credentials issued at runtime instead of stored secrets
- Blended Identity combining agent attestation with human IdP context
- Customizable MCP Identity Gateway enforcing agent access to MCP servers
- Tool filtering to allow or block individual agent tools
- AI kill switch and one-click revocation of a single agent's access
- On-behalf-of token handling with delegation vs. impersonation semantics
- Fully attributed audit trail separating agent-initiated from human-initiated actions
- Runtime policy enforcement evaluated on every access request
- Conditional Access on risk signals from CrowdStrike and Wiz posture
- Workload Identity Federation for cloud services including Claude and OpenAI
- Coverage for workforce, autonomous, B2B, consumer, and endpoint agents
- Traditional workload support for Kubernetes, AWS Lambda, and CI/CD pipelines
- Supports OIDC, OAuth 2.1, SPIFFE, Kerberos, WIF, and XAA / ID-JAG with no proprietary SDK
- Deployment across cloud, SaaS, and on-prem data centers
About Aembit
Aembit is an identity and access management control plane for non-human identities — AI agents, MCP servers, and service-to-service workloads. Rather than handing an agent a long-lived API key, you write a policy and Aembit issues a short-lived, scope-limited credential at request time. The free Starter tiers cover 3 AI agents or 10 workloads; the Teams tiers run $20/agent/mo and $20/workload/mo, and Enterprise tiers are quoted custom. Four mechanics do the work. Blended Identity evaluates the agent's attested identity alongside the human or process that authorized it, so an agent gets a scoped subset of a person's rights instead of their standing access — Aembit's own framing is that borrowing a human identity without that check is impersonation, not delegation. Runtime policy enforcement re-decides on every request, so there are no bootstrap credentials and no shared service accounts. The customizable MCP Identity Gateway enforces policy on agent access to MCP servers, with tool filtering so a read-only agent stays read-only. The AI kill switch revokes a single agent's access in a click without disturbing the employee's session. The same control plane spans workforce agents (Copilot Studio, Claude, ChatGPT, Meta Muse), autonomous and B2B agents with nobody in the loop at request time, endpoint coding assistants, and classic targets like Kubernetes, AWS Lambda, and CI/CD pipelines. It augments OIDC, OAuth 2.1, SPIFFE, Kerberos, WIF, and XAA / ID-JAG rather than replacing them, so there is no proprietary SDK to adopt. Every decision lands in an audit trail attributed to one identity. Security and platform teams pushing agents into production are the buyer, especially regulated shops that have to prove which actions were agent-initiated versus human. Aembit cites a CSA survey figure that 68% of organizations can't distinguish AI agent activity from human activity — that number is the pitch. Against HashiCorp Vault it is deeper on agent identity but shallower as a general secrets store; against DIY SPIFFE plus a vault it is faster to operate but commercial.
Behind the Verdict
Aembit is one of the clearer answers to a problem most organizations discover late: an AI agent acting on a user's behalf inherits that user's standing permissions, and the resulting log line is indistinguishable from a human action. Aembit's Blended Identity attacks that by evaluating the agent's attested identity and the authorizing human together on every decision, so the log attributes the action to the agent and records on whose behalf it ran. Everything else in the product hangs off that. Strengths: runtime issuance of short-lived scoped credentials removes the long-lived API key sprawl that accumulates around agent projects; the MCP Identity Gateway with tool filtering is a genuinely narrow capability that maps to a real gap — most MCP deployments have no per-tool policy; and the kill switch gives you a single-agent revocation that doesn't require disabling the employee's session. Standards support matters too: OIDC, OAuth 2.1, SPIFFE, Kerberos, WIF and XAA / ID-JAG with no proprietary SDK means you're not rewriting the agents you already shipped, and the January 2026 blog entry on impersonation versus delegation shows they're working the token-semantics edge cases rather than hand-waving them. Weaknesses: this is a control plane, not a model, so its value is entirely dependent on plugging it into an IdP you already run and the agent platforms you actually use — there's no partial adoption. Pricing is one-dimensional per-agent or per-workload, which is clean at ten agents and starts to need a conversation at 500. Conditional Access and 24x7 support sit behind Enterprise, so risk-signal-driven enforcement from CrowdStrike or Wiz posture is not a Teams-tier capability. And teams that have never run SPIFFE or workload identity will find the concepts — attestation, trust providers, blended vs. delegated identity — a real ramp. Where it fits: a regulated enterprise standing up Claude, Copilot Studio or custom MCP-backed agents against production systems, where the deliverable is an audit artifact showing agent-versus-human attribution. Where it doesn't: a shop that just wants to stop rotating static secrets between three services, or an open-source-first team committed to hand-assembling SPIFFE plus Vault. The later one isn't a knock on Aembit — it's a different budget line.
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Real-world workflow fit
Concrete scenarios for the personas Aembit actually fits — and what changes day-one when you adopt it.
Your Claude agents are being rolled out to staff against production Snowflake data. You connect your existing IdP, enable Blended Identity so each agent is evaluated with the employee who authorized it, and route MCP server access through the MCP Identity Gateway with read-only tool filtering.
Outcome: Every agent action lands in the audit trail attributed to the agent and the authorizing human, which is the artifact your SOC 2 and internal review teams were asking for.
You replace static credentials between Kubernetes services, AWS Lambda functions, and CI/CD pipelines with runtime-issued short-lived tokens, keeping your existing OIDC provider rather than adopting a proprietary SDK.
Outcome: No standing secrets to rotate, and the Workloads Starter tier at 10 workloads is enough to prove it out before committing to $20/workload/mo.
Staff connect ChatGPT, Claude, and Meta Muse to work resources. When one agent starts behaving oddly, you hit the kill switch for that agent rather than disabling the employee's account.
Outcome: One agent loses access immediately, the employee keeps working, and the revocation is recorded against the agent's identity.
Use Cases
- Give every Microsoft Copilot Studio agent a unique blended identity instead of a shared service account
- Deploy Claude or OpenAI agents across a workforce while enforcing per-agent access policy
- Enforce policy-based access from AI agents to MCP servers and internal tools, including per-tool filtering
- Replace long-lived API keys for OpenAI and Claude with short-lived federated tokens
- Enforce least-privilege for service-to-service traffic across Kubernetes, Lambda, and CI/CD
- Cut secret rotation effort by removing standing credentials from workloads
- Produce audit-ready logs of every agent and workload access decision for SOC 2, HIPAA, or PCI DSS review
- Cut off a misbehaving or compromised agent in one click without waiting for a review cycle
Models Under the Hood
as of 2026-10-16
Limitations
- Aembit is an identity and access management control plane for AI agents, MCP servers, and non-human workloads — not a standalone AI model — so its value depends on integrating with your existing IdP and the agent or workload systems it brokers access to.
- Pricing is per agent or per workload, so cost scales linearly with deployment size.
- Conditional Access and 24x7 support sit on the Enterprise tier, so risk-signal-driven enforcement requires a custom quote.
- The Teams tiers list 10 agents (growing to 500) and 10 workloads (growing to 50), so larger fleets hit Enterprise.
- Blended identity, attestation, and delegation-vs-impersonation semantics carry a genuine learning curve for teams accustomed to static API keys.
as of 2026-10-19
Verification history
We have re-verified Aembit 19 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
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Free to cite with attribution — this page re-verifies continuously.
12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
Where the pricing makes sense
The company stage and team size where Aembit's pricing actually pencils out — and where peers do it cheaper.
Priced for a single team: $20/agent/mo on Agentic AI Teams and $20/workload/mo on Workloads Teams, both of which you get to try free at 3 agents / 10 workloads. That lands between free open-source SPIFFE-and-vault assembly (cheap in license, expensive in engineer weeks) and enterprise non-human IAM suites sold on annual contracts. At 500 agents the per-unit model stops being obviously cheapest — that's the Enterprise conversation.
Setup time & first value
How long it actually takes to get something useful out of Aembit — broken out by persona, not the marketing-page minute.
If you already have an OIDC-capable IdP, the free Starter tenant is self-serve and a first policy against a test workload is a same-day exercise. Getting to real value — Blended Identity across a live agent fleet plus the MCP gateway — realistically runs a few weeks of platform and security time, mostly spent mapping which agents and MCP servers exist. Teams with no prior workload-identity
Switching to or from Aembit
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From long-lived API keys for OpenAI/Claude: swap stored keys for federated short-lived tokens issued at runtime, keeping the same agent code paths.
- →From HashiCorp Vault service accounts: keep Vault for secrets storage and add Aembit in front for agent and workload access decisions, rather than ripping Vault out.
- →From DIY SPIFFE plus a vault: Aembit augments SPIFFE workload attestation, so existing SVIDs and trust domains can inform policies instead of being rebuilt.
- ↗To HashiCorp Vault: export access policies as Vault policy definitions and move credential issuance back to Vault's secrets engines — expect to lose per-request blended identity attribution.
- ↗To a DIY SPIFFE stack: stand up SPIRE, re-encode Aembit policies as authorization policy, and rebuild the audit trail from your own logs.
Integrations
Resources & Guides
Tutorials & Learning
YouTube returned 6 videos for “Aembit”, and we withheld 6: 6 could not be judged, because “Aembit” is a single word that other videos use for other things. We are showing none, because we could not prove any of them are about Aembit.
Official links
Tools that pair well with Aembit
Common stack mates teams adopt alongside Aembit, with the specific reason each pairing earns its keep.
Cyera
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SailPoint
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Cyberhaven
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Alternatives to Aembit
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Cyera
Cyera is an AI security platform that unifies data security posture, DLP, non-human identity and AI agent governance in one control plane.
SailPoint
Enterprise identity security and governance for human, machine, and AI agent identities
Cyberhaven
Data lineage DLP that follows sensitive data through humans and AI agents, so leaks get caught wherever content is pasted, copied, or rewritten.
Frequently Asked Questions
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