Public-source research
Vendor evidence
Review what vendors say publicly, the exact quoted source text, the security requirement each statement may support, and what still needs verification.
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Evidence records1280
Source checked863
Needs verification0
Source captured0
No supporting claim found411
Excluded from evidence6
Aembit claims centralized agent access policy, cryptographically verifiable identity, per-request policy decisions, and audit logs tying agent identity, user identity, target server, credential, and resource access together.
Every MCP request is logged with agent identity, user identity, target server, and policy decision.
Related framework references (5)
Aembit identity and access management (IAM) for Agentic AI materials reviewed did not provide a public product claim for automated adversarial testing, repeatable attack suites, model or agent red teaming, or release-gate evaluation.
No quoted source text is recorded for this claim.
Related framework references (5)
Aembit identity and access management (IAM) for Agentic AI materials reviewed did not establish model artifact scanning, provenance, signing, dependency or Model Context Protocol (MCP) component analysis, tamper detection, or model-registry release controls.
No quoted source text is recorded for this claim.
Related framework references (5)
Aembit claims an Model Context Protocol (MCP) Identity Gateway that validates workload identity, enforces per-request policy, approves or denies access, exchanges credentials, and logs agent-to-resource communications.
The gateway authenticates the agent, enforces policy, and performs token exchange.
Related framework references (5)
Aembit claims cryptographically verified blended agent and user identity, OAuth 2.1 authorization, secure token exchange, ephemeral just-in-time credentials, least privilege, immediate revocation, and full access attribution.
Aembit IAM for Agentic AI assigns each agent a cryptographically verified identity, issues ephemeral credentials, enforces policy at runtime.
Related framework references (5)
Aembit identity and access management (IAM) for Agentic AI materials reviewed did not establish governance of coding-agent commands, developer-workstation files or networks, integrated development environment (IDE) extensions, skills, hooks, secrets, or package actions.
No quoted source text is recorded for this claim.
Related framework references (5)
Aembit materials reviewed did not provide a public claim for employee AI app discovery, unapproved AI usage discovery, prompt/user activity inventory, or AI domain detection.
No quoted source text is recorded for this claim.
Related framework references (5)
Aembit materials reviewed did not provide a public claim for software as a service (SaaS) AI inventory, embedded software as a service (SaaS) AI features, or third-party AI service monitoring.
No quoted source text is recorded for this claim.
Related framework references (5)
Aembit claims policy, context, and audit for all agent interactions based on unique identities.
Aembit enforces access to your sensitive data and accelerates your AI use with confidence. Apply policy, context, and audit to all agent interactions based on their unique identities.
Related framework references (5)
Aembit claims the ability to stop AI access and audit access in real time based on an agent's unique identity.
Stop AI access with a click of a button. Audit access in real-time — based on the agent’s unique identity, even if it’s operating on behalf of a user.
Related framework references (5)
Aembit claims policy-based, secretless, identity-driven access between AI agents and sensitive resources across clouds, software as a service (SaaS), and on-premise environments.
Aembit enforces policy-based, secretless, identity-driven access between workloads, AI agents, and the sensitive resources they need — across clouds, SaaS, and on-premise environments.
Related framework references (5)
Aembit materials reviewed did not provide a public claim for browser extension enforcement, enterprise browser controls, software as a service (SaaS)-session controls, or user activity policy.
No quoted source text is recorded for this claim.
Related framework references (5)
Aembit claims policy-based, identity-driven controls for AI agents accessing large language models (LLMs), application programming interfaces (APIs), and tools.
Streamline and secure access from AI agents to leading LLMs like OpenAI, Claude, and Gemini, APIs, and tools with policy-based, identity-driven controls.
Related framework references (5)
Aembit claims full attribution for every agent action with audit logs that distinguish human-initiated and agent-initiated access.
Full attribution for every agent action – audit logs definitively distinguish human-initiated access from agent-initiated access
Related framework references (5)
Aembit claims Model Context Protocol (MCP) Authorization enforces policy-based controls over which agents can reach which tools and data.
Aembit secures access between AI agents and MCP (Model Context Protocol) servers, enforcing policy-based controls over which agents can reach which tools and data.
Related framework references (5)
Aembit claims non-human identity (NHI) coverage for AI agents, application programming interfaces (APIs), microservices, CI/CD pipelines, scripts, and service accounts with dynamically issued short-lived credentials.
non-human identities (NHIs) — including AI agents, APIs, microservices, CI/CD pipelines, scripts, and service accounts
Related framework references (5)
Aembit materials reviewed did not provide a public claim for AI spend attribution, model cost routing, budget enforcement, rate limits, runaway token controls, or AI return on investment (ROI) reporting.
No quoted source text is recorded for this claim.
Related framework references (5)
Aembit publishes an Agentic AI Teams tier priced at $20 per agent per month.
Teams $20 /agent/mo Perfect for an individual team running a set of agents in production.
Related framework references (2)
Aembit claims policy-based, identity-driven controls for AI agents accessing OpenAI, Claude, Gemini, application programming interfaces (APIs), and tools.
Streamline and secure access from AI agents to leading LLMs like OpenAI, Claude, and Gemini, APIs, and tools with policy-based, identity-driven controls.
Related framework references (5)