Aembit
Policy-driven, secretless access control for AI agents and workloads
Aembit is the strongest choice we've seen for teams deploying AI agents in production who need audit-ready, policy-based access without coding auth. The AI kill switch and blended identity are genuinely differentiating, and the recent OpenAI federation support extends its reach. It's overkill for a handful of static service accounts, and the per-agent pricing can climb fast at scale. If you're a small team with a few workloads, a simpler tool like HashiCorp Vault might suffice. But for enterprise-grade agentic AI access, Aembit stands out against open-source DIY stacks.
Verified 9d ago · liveness 69/100 · cite: rightaichoice.com/tools/aembit
- Securing AI agents (like Claude, OpenAI, or Copilot Studio) accessing enterprise resources
- Replacing secrets managers and DIY identity systems for workloads
- Centralized IAM for non-human identities across multi-cloud and on-prem
- Teams needing audit-ready, policy-based access for agentic AI
- Organizations requiring fully self-hosted, air-gapped IAM solutions
- Simple use cases with only a few static service accounts
- Teams that prefer open-source identity tools (e.g., SPIFFE, OAuth2 Proxy)
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Skip Aembit if you need a fully self-hosted, air-gapped IAM solution, or if you only have a handful of static service accounts and don't need agentic AI identity management.
The Teams tier costs $20/workload/mo and $20/agent/mo, which can add up quickly if you have many workloads or agents.
Aembit's per-workload and per-agent pricing fits organizations deploying AI agents at scale, where the cost of a security incident or compliance failure outweighs the per-agent fees. Compared to open-source tools that require significant DevOps effort, Aembit's paid tiers may be justified. However, for small teams with a few workloads, the free tier is generous, but the Teams tier at $20/workload/mo is pricier than some alternatives like HashiCorp Vault's open-source version, though it offers
In short
Aembit — Policy-driven, secretless access control for AI agents and workloads. Best for Securing AI agents (like Claude, OpenAI, or Copilot Studio) accessing enterprise resources, Replacing secrets managers and DIY identity systems for workloads, Centralized IAM for non-human identities across multi-cloud and on-prem. Free to start; paid plans from $20/mo.
What's new in Aembit
Checked 9 days agoAcross the latest 2 updates: 2 feature updates.
Aembit IAM for Agentic AI now supports Microsoft Copilot Studio
Aembit extends IAM for Agentic AI to Microsoft Copilot Studio, giving every agent a unique blended identity.
OpenAI Workload Identity Federation: Aembit Brings Secretless Access to the OpenAI API
Aembit adds an OpenAI Workload Identity Federation Credential Provider, replacing static keys with short-lived tokens.
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: September 2026
How we score →Key Features
- Secretless authentication for AI agents and workloads
- Policy-based short-lived credential issuance
- AI kill switch to stop agent access with one click
- Real-time audit logging for agent actions
- Support for MCP, A2A, OAuth, OIDC, SPIFFE, Kerberos
- Blended Identity via human IdPs (user + client context)
- Workload identity discovery and exploration
- Integration with CrowdStrike for security posture
- Integration with Wiz for access policy intelligence
- Flexible authentication across AWS, Azure, GCP, on-prem, SaaS
- Centralized policy control plane
- Conditional access and MFA for agents
- Workload Identity Federation for Claude API and OpenAI API
- MCP server creation guidance for LLM integration
- Support for Microsoft Copilot Studio agents
About Aembit
Aembit is a cloud-native Identity and Access Management (IAM) platform built specifically for agentic AI and non-human workloads. It replaces the messy tangle of secrets managers and DIY identity scripts with a centralized control plane that enforces policy-based, short-lived access. You can authenticate AI agents—whether delegated, autonomous, or chained—and enforce access policies in real time, with no code. Aembit supports a wide range of authentication standards including OAuth, OIDC, SPIFFE, Kerberos, and recent additions like Workload Identity Federation for the OpenAI API and Claude API, plus integration with Microsoft Copilot Studio. It works across AWS, Azure, GCP, on-prem, and SaaS environments, and is SOC2 and ISO27001 certified. The platform gives security teams a single pane of glass to define access policies, apply dynamic context and MFA for agents, and audit every access. The AI kill switch lets you stop agent access with one click, and audit logs provide a single source of truth, distinguishing human-initiated from agent-initiated actions. Recent updates added support for OpenAI Workload Identity Federation, replacing static keys with short-lived tokens, and Microsoft Copilot Studio integration. Customer stories highlight measurable outcomes: Snowflake saved 2 FTEs and cut 85% of credential issuance, and Red Cup IT secures autonomous agents in customer environments. Aembit scales to billions of transactions, making it suitable for enterprises with tough compliance requirements. Compared to open-source tools or raw secrets managers, it offers a production-grade, policy-driven approach without the operational burden.
Behind the Verdict
Aembit fills a genuine gap in the IAM market: non-human identities. It's not just a secrets manager; it's a policy-driven control plane that treats AI agents and workloads as first-class citizens, with their own identities, context, and audit trails. For engineering teams, the promise of 'no auth coding' is real—Aembit handles secretless authentication and short-lived credential issuance automatically, letting developers focus on building. For security teams, the centralized visibility, real-time audit, and one-click kill switch are major wins, especially for compliance. The recent additions—OpenAI Workload Identity Federation and Copilot Studio support—show the platform is evolving with the agentic AI wave. Strengths: The AI kill switch is a standout feature; it's not just a kill switch but a full access-revocation mechanism tied to identity. Blended Identity, combining user context from IdPs with client context, provides granular control that's hard to achieve with traditional IAM. Standards support is broad (OAuth, OIDC, SPIFFE, Kerberos) and it works across major clouds and on-prem, so you can adopt it without ripping out existing systems. The free tier is generous enough to test real use cases. Weaknesses: Pricing is per-workload and per-agent, which can get expensive as you scale—especially the Teams tier at $20/agent/mo, which could surprise teams with many agents. The free tier has limited event log retention (24 hours) and only 10 workloads or 3 agents, so you'll hit walls quickly in production. It's a SaaS platform; if you require air-gapped, fully self-hosted IAM, Aembit won't fit. Also, there's a learning curve for non-technical users, though the no-code policies help. Where it fits: Enterprises deploying AI agents at scale (Claude, OpenAI, Copilot Studio) into production, with compliance requirements and a mix of cloud and on-prem resources. Also great for teams currently juggling multiple secrets managers and DIY scripts. Where it doesn't fit: small teams with a handful of static service accounts, or those needing fully on-prem IAM. Bottom line: Aembit is a purpose-built tool for a modern problem. If you're serious about securing agentic AI, it's worth a serious look.
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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.
You need to secure access for AI agents like Claude that access sensitive data.
Outcome: Set up Aembit, create a policy for the agent, and enforce short-lived credentials. You can audit access in real-time and kill access with one click if needed.
You want to eliminate static secrets in your pipeline.
Outcome: Integrate Aembit with your CI/CD to issue short-lived tokens via Workload Identity Federation, reducing secret leakage risk.
You need to secure agentic AI that operates in customer environments.
Outcome: Use Aembit's Blended Identity to ensure each agent has a unique identity, and enforce policies across multiple customer environments with full audit.
Use Cases
- Automate least-privilege policy enforcement for all non-human identities across multi-cloud environments
- Monitor real-time workload access logs to detect anomalous credential usage and potential breaches
- Integrate with Okta to extend zero-trust policies from human users to service accounts and API keys
- Rotate secrets across thousands of workloads without downtime using HashiCorp Vault integration
- Audit every workload-to-workload interaction for compliance with SOC 2, HIPAA, or PCI DSS
- Secure Microsoft Copilot Studio agents with unique blended identities
- Deploy Claude across your workforce while enforcing access policies
- Ensure secure access from AI agents to MCP servers via policy
Models Under the Hood
as of 2026-08-31
Limitations
- Aembit's pricing is per-workload and per-agent, which can become expensive as you scale, especially beyond the free tiers.
- The free Starter plans limit you to 10 workloads or 3 agents with only 24 hours of event log retention, so production use requires a paid tier.
- The platform is cloud-native SaaS; on-premises deployment is not supported.
- There is a learning curve for non-technical users, though the no-code policies help.
- Also, while it supports many standards, some advanced features like conditional access are only in Enterprise.
as of 2026-08-28
Verification history
We have re-verified Aembit 16 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
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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.
Plans compared
For each published Aembit tier: who it actually fits, and what it adds vs. the previous tier. Cross-reference the cost calculator above for projected annual outlay.
Workloads Starter
$0/mo
Ideal for
Small projects or evaluation with up to 10 workloads and 10 policies.
What this tier adds
Free entry point for workloads, includes 10 workloads, 10 policies, 24-hour log retention, community support.
Agentic AI Starter
$0/mo
Ideal for
Teams testing agentic AI with up to 3 agents and basic MCP gateway.
What this tier adds
Free entry point for agents, includes Blended Identity via human IdPs, single MCP gateway, 5 MCP policies.
Workloads Teams
$20/workload/mo
Ideal for
Individual teams running a set of services in production, needing live support.
What this tier adds
$20/workload/mo, grows to 50 workloads, adds live support during business hours.
Agentic AI Teams
$20/agent/mo
Ideal for
Teams running up to 10 agents in production with more extensive MCP needs.
What this tier adds
$20/agent/mo, grows to 500 agents, customizable MCP gateway, unlimited policies, 7-day logs, live support.
Workloads Enterprise
Custom
Ideal for
Organizations needing unlimited workloads, conditional access, and 24x7 support.
What this tier adds
Custom pricing, includes unlimited workloads and policies, custom log retention, conditional access, 24x7 support.
Agentic AI Enterprise
Custom
Ideal for
Enterprises scaling agentic AI access across development, QA, and production.
What this tier adds
Custom pricing, includes unlimited agents, custom MCP gateway, unlimited policies, custom logs, conditional access, 24x7 support.
Where the pricing makes sense
The company stage and team size where Aembit's pricing actually pencils out — and where peers do it cheaper.
Aembit's per-workload and per-agent pricing fits organizations deploying AI agents at scale, where the cost of a security incident or compliance failure outweighs the per-agent fees. Compared to open-source tools that require significant DevOps effort, Aembit's paid tiers may be justified. However, for small teams with a few workloads, the free tier is generous, but the Teams tier at $20/workload/mo is pricier than some alternatives like HashiCorp Vault's open-source version, though it offers
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.
For a basic setup with a few workloads or agents, you can get an Aembit tenant and configure policies in under an hour. Integrating with your IdP and first workload takes about half a day. For more complex environments with multiple clouds and MCP servers, plan for a few days to a week depending on your existing identity infrastructure.
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 HashiCorp Vault: Aembit can work alongside Vault, and you can gradually migrate to Aembit for policy-based access while keeping Vault for other secrets.
- →From DIY scripts: You can replace hardcoded credentials with Aembit's secretless authentication, eliminating the need to manage scripts.
- ↗To HashiCorp Vault: Export your policies and manually recreate them if you need a self-hosted solution.
- ↗To open-source tools: You can extract audit logs and policies, but you'll need to rebuild the control plane yourself.
Integrations
Resources & Guides
Tutorials & Learning
Official links
Tools that pair well with Aembit
Common stack mates teams adopt alongside Aembit, with the specific reason each pairing earns its keep.
SailPoint
Enterprise-grade identity governance securing humans, machines, and AI agents with adaptive access controls
Nightfall AI
AI-native DLP platform to control data across AI agents, MCP servers, endpoints, and SaaS.
Veza
Identity security platform unifying access visibility, governance, and least privilege enforcement across hybrid cloud, SaaS, and AI agents
Alternatives to Aembit
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SailPoint
Enterprise-grade identity governance securing humans, machines, and AI agents with adaptive access controls
Nightfall AI
AI-native DLP platform to control data across AI agents, MCP servers, endpoints, and SaaS.
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