Control infrastructure for enterprise AI agents.

AethosHub builds self-hosted software for governing how AI agents and applications access model providers. Protect provider credentials, enforce runtime policies, control spend and routing, and maintain auditable activity while keeping deployment and provider accounts within your environment.

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EnterpriseGrade Security

ScalableArchitecture

AuditableActivity Records

Agent Governance

One governed control layer between AI agents and enterprise systems.

Agent Access Manager is a self-hosted AI gateway that governs how agents and applications access model providers. Workloads authenticate with scoped, revocable credentials while reusable provider secrets remain encrypted and hidden from agent code.

Every model request can be evaluated against key, project, team, model, budget, rate, and guardrail policies before it is forwarded. Model aliases and provider configuration keep routing decisions out of application code.

Model-generated tool-call arguments can be screened with configured flag or block policies before the application receives them. Tool execution authorization remains in the agent runtime or tool service. Agent Access Manager records model-call, usage, outcome, and guardrail events for operational review.

Agent Access01 / 06

Scoped agent access

Identify agents and applications through revocable credentials associated with owners, teams, environments, and access policies.

Scoped access context

Credential Security02 / 06

Credential protection

Store provider credentials encrypted and inject them only when governed model requests are forwarded. Agents do not receive reusable provider keys.

Protected credentials

Access Policy03 / 06

Runtime authorization

Authenticate model requests with scoped virtual keys and apply the key, project, team, and organization policy chain before forwarding calls.

Request authorization

Activity Records04 / 06

Auditable activity

Record governed model requests, provider selection, usage, configured cost, guardrail findings, and outcomes handled through Agent Access Manager.

Operational audit trail

Policy Enforcement05 / 06

Runtime guardrails

Apply configured policies for content, PII, secrets, spend, rate limits, and model-generated tool-call arguments to requests and responses.

Configured guardrails

Provider Reliability06 / 06

Health-aware routing

Route model aliases across configured deployments, cool down repeatedly failing targets, and try eligible fallbacks for supported non-streaming calls.

Provider routing

AI Agents

Connect coding agents to governed models

Connect internally developed agents

Control agent-to-model communication

Attribute model usage by application

Agent Access Manager

Authenticate agents with scoped credentials

Authenticate model requests by scope

Keep provider credentials hidden from agents

Enforce guardrails before forwarding requests

Record policy decisions and outcomes

Enterprise Systems

Connect approved cloud providers

Govern OpenAI-compatible endpoints

Route to Anthropic deployments

Route to self-hosted model servers

Connect Gemini and Vertex AI

Products

Central control for your AI infrastructure.

Flagship platform

agentaccessmanager.com

Agent Access ManagerBy AethosHub

One governed gateway for model-provider access. Provider credentials remain hidden from agents.

Agent Access Manager runs in your environment between AI applications, agents, and model providers. Applications use an OpenAI-compatible endpoint and scoped virtual keys while the platform routes requests, protects provider credentials, enforces policies, and records governed model activity.

Scoped virtual access

Create revocable, provider-independent virtual keys for applications, teams, and agents. Provider credentials remain encrypted and are not returned to clients.

Compatible model access

Connect OpenAI-compatible clients to the gateway, use model aliases, and reduce provider-specific integration changes.

Health-aware routing

Route model requests through configured providers and fail over when a provider or deployment becomes unavailable.

Budgets and rate controls

Enforce spend budgets and RPM/TPM limits across organizations, teams, projects, and keys.

Request and response guardrails

Apply configured PII, secret, pattern, and content policies to requests and responses with allow, flag, redact, or block actions.

Tool-call argument screening

Flag or block configured findings in model-generated tool-call arguments before application-side tool execution.

Security visibility

Maintain searchable model-call and guardrail records for operational investigation, security detection, and response workflows.

Explore Agent Access Manager

app.ts — OpenAI-compatible client example

const client = new OpenAI({
  baseURL: "https://gateway.acme.com/v1",
  apiKey: process.env.VIRTUAL_KEY,  // not a vendor key
});

const reply = await client.chat.completions.create({
  model: "fast",  // your alias — routed, metered, guarded
  messages: [{ role: "user", content: "Review this contract." }],
});

OpenAI-compatibleSelf-hostedConfigurable base URL

ProductComing soon

apikeyops.com

Centralize ownership and lifecycle visibility for enterprise AI credentials.

APIKeyOps provides a governed inventory of provider credentials, their owners, lifecycle status, and available usage information. It helps security and platform teams identify unmanaged credentials, assign accountability, and maintain an auditable operational record.

Credential inventory

Track provider credentials as governed assets with ownership and lifecycle status.

Ownership and accountability

Associate credentials with the teams, projects, and environments responsible for their use.

Usage visibility

Attribute available provider usage and cost information to the appropriate credentials and owners.

Lifecycle oversight

Track expiry, rotation, stale, and revoked states where supported by the configured provider integration.

Audit history

Record security-relevant credential events to support internal security and compliance reviews.

APIKeyOps coming soon

Integrations

Connect model providers and agent frameworks through one governed layer.

Bring supported model providers, OpenAI-compatible endpoints, and agent frameworks behind a consistent gateway. Centralize routing, credentials, policies, and audit visibility without rebuilding governance separately for every application.

LLM Provider Support

Leading model providers through governed connections.

Connect OpenAI-compatible endpoints, Anthropic, Gemini, Vertex AI, and supported self-hosted models through centrally managed provider configurations and model aliases.

OpenAIAnthropicAzure OpenAIAWS BedrockGoogle GeminiVertex AICohereMistral AIGroqOllamaMeta LlamaIBM watsonxNVIDIADatabricksDeepSeek

Additional providers can connect through supported OpenAI-compatible endpoints.

Framework Support

Works with OpenAI-compatible clients and common agent frameworks.

Connect SDKs, frameworks, internal wrappers, and AI applications that support a configurable OpenAI-compatible endpoint.

LangChainLangGraphLlamaIndexDSPyVercel AI SDKLiteLLMSemantic KernelOpenAI SDKCrewAIAGAutoGen

Integration typically requires configuring the Agent Access Manager base URL and a scoped virtual key.

See supported integrations

Standardize security across your entire AI infrastructure.

Talk directly with the engineers who build Agent Access Manager. We will review your model providers, agent workflows, deployment environment, identity, and security requirements, then map them to a practical control architecture.

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We typically respond within one business day.