AI agent orchestration platform

Put your agentic workforce under your control.

Run AI agents, automations and integrations inside your own infrastructure, under your single sign-on, your approval chains, your spend caps and your audit log. You see every run while it happens, approve the steps that matter, and keep an audit trail you can hand to a reviewer.

Start now See the control room

Going agentic should not cost you your compliance posture.

Agent operationsSSO · your identity provider
Active runs7
Awaiting you1
Spend today$18.40
release-engineerimplementing CRI-2841 in a sandbox$2.14 / $20
ops-analystwants to post a reply on 3 customer tickets
Tool · jira.comment · approval required
market-scoutreading 12 feeds · read-only credentials$0.08 / $5
decision-keeperrecorded a decision · CTA colour by marketlogged
14:22:07 approval.granted approver@yourcompany args=edited→ your SIEM
  • See it

    Every AI agent, every run, every step. Live while it happens, replayable after.

  • Gate it

    Human-in-the-loop approvals written into the agent and enforced by the platform, not the prompt.

  • Cap it

    Spend limits per run, per hour and per day. The run parks at the ceiling and never surprises you.

  • Log it

    An append-only record of who approved what, delivered to your SIEM.

  • Own it

    Your Kubernetes, your identity provider, your data. Air-gapped if that is the rule.

Agentic AI in production

What your AI agents actually finish.

Every job below runs end to end on the platform today, with human approval at the points you choose.

  • InSomeone replies to your brand's post on X.OutSentiment analysis across the whole thread, and a reply drafted for your approval.
  • InA supplier invoice lands in your finance inbox.OutThe payment prepared in Stripe, held for your sign-off, then executed and logged.
  • InA product owner describes what they need, in plain language.OutAn application live on your domain, with a database and monitoring.
AI agent observability

Watch what every AI agent is doing, while it is doing it.

Every agent run streams as it happens: each step, each tool call, each approval. Anything waiting on a human sits at the top, and the whole run replays once it is done.

Your agents12 defined · 4 on duty
release-engineerv7 · 94% success · 41 min medianRunning
ops-analystv3 · parked, waiting on youNeeds you
market-scoutv2 · read-only · no write tools grantedRunning
decision-keeperv5 · idle · 340 decisions on recordIdle
Spend, today
$18.40cap $200.00 · parks at the limit
release-engineerrun 9f2cCRI-2841 · started 13:41
  1. plan

    14 tasks drafted, approved by you at 13:43

  2. sandbox

    isolated workspace, no egress beyond your allow-list

  3. changes

    31 files, 2 database migrations

  4. tests

    214 passed, 0 failed

  5. output guardrail

    no customer data in the diff, passed

  6. gate

    open a pull request, waiting for a second approver

Acting as

A GitHub account scoped to one repository, issued from your Vault.

If it goes wrong

Replay the run step by step, or revoke the credential in one click.

The audit trail
13:43:11 plan.approved approver@yourcompany run=9f2c14:22:07 tool.approved approver@yourcompany tool=jira.comment args=edited14:22:09 credential.used ref=vault://projects/atlas secret=not-logged

Append-only, with before and after state, posted to your SIEM by webhook.

Human-in-the-loop approvals

No AI agent acts without the approval you asked for.

Governance is part of the agent definition, enforced by the platform on every turn and recorded in the audit log. These are not instructions in a prompt that a model may decide to ignore.

Input and output guardrails

Expression checks, model-judged rubrics, or a whole workflow as the check, with retry on fail.

Runs on every turn, before anything leaves the agent

Tool approvals you can edit

Never, always, or when a condition holds; assignees, quorum and timeout. The approver can rewrite the arguments before saying yes.

You sign off on the call, and on what it carries

Budget gates

Maximum iterations and cost per run. When a limit is reached the run parks for a decision and stops there.

You sign off on spending past the limit

Approvals inbox and Telegram

Decide on the web or from an inline keyboard. Unanswered approvals age into a dead-letter queue you can redrive.

Nothing waits silently

Audit log to your SIEM

Every approval, credential event, decision and skill action is recorded with before and after state, and can be delivered by webhook.

Append only. Nobody edits the record

MicroVM sandboxes

Coding, browser and desktop agents run in Kata Containers with egress policies, non-root execution and read-only root filesystems.

An agent cannot reach what you did not grant it

AI cost controls

Your AI agents cannot spend what you did not allow.

Limits are set per run, per hour and per day, on cost, LLM tokens or calls. When one is hit the run parks for a decision or fails. It never quietly keeps going.

Spend controlsorg · project · agent
  • Per run$20.00 · 40 iterations
  • Per hour$60.00 across the org
  • Per day$200.00 across the org

Park, do not surprise

At the limit a run stops and waits for a human decision, or fails outright, whichever you configured. No run bills past its ceiling.

Forecast before you commit

Per-session cost forecasts, burn-rate telemetry, org budgets and quotas, with CSV export for whoever owns the number.

Your keys, your rates

Bring your own provider keys, route each stage of work to a different model, and fail over automatically when one provider has a bad day.

Integrations and connectors

Your AI agents connect to the systems you already run.

Your agents act through credentials your own Vault issues and can revoke, scoped to one repository, one project, one mailbox. Not a shared key that opens everything.

  • Social & publishing
  • Git & CI
  • Ticketing & projects
  • Chat & messaging
  • Email & SMS
  • CRM & marketing
  • Files & documents
  • Databases & data
  • Cloud & identity
  • Security & ops
  • Commerce & finance

Least-privilege connected accounts

The accounts an agent acts through are granted per project with the narrowest scopes that work, and sensitive actions still need an owner's approval.

Gmail · Google Calendar · Google Drive · Slack · Discord · Jira · Facebook Pages · Instagram · TikTok · X

Drive it from your editor

Crios is an MCP server: start work, steer a session, publish and run automations from Claude Code, Cursor or Claude Desktop, authenticated with a token you can revoke.

See the whole platform

More than 250 integrations ship with the platform, and anything without a dedicated one reaches through a plain HTTP step, so an internal service is never a blocker.

Self-hosted AI infrastructure

Your AI runs on your side of the boundary.

Your code, your data, your secrets and your audit trail stay where they already live. The whole platform is one Helm chart on any Kubernetes, on-premises or air-gapped. The only traffic that has to leave goes to your model providers, and those can be yours too.

Your Kubernetes, one Helm chartnothing inside this line leaves
  • Orchestratorcontrol plane
  • Agent sandboxesa microVM per session
  • Your sourcegit, in cluster
  • Secretsnever in a log
  • Project databasesone role per project
  • What it learnsvector store, yours
  • Web searchself-hosted
  • Audit trailto your SIEM
OutsideYour model providers

Anthropic, OpenAI, Gemini and the rest, or an endpoint on your own hardware, which closes the boundary completely.

Kata microVMs

The hypervisor is the trust boundary for coding, browser and desktop sandboxes.

Two-database boundary

Control plane and per-project databases are separate instances with separate roles.

Vault-backed secrets

Credentials are references; secret material never enters definitions, journals or logs.

SSO, MFA, RBAC

OIDC single sign-on, TOTP with backup codes, roles, groups and scoped personal tokens.

Audit log and SIEM webhook

Append-only actions with before/after state, delivered to your security tooling.

Backups and DR

Scheduled backups to S3-compatible storage, restore drills and retention policies.

Air-gap friendly

Postgres, Redis, vector search, git, Vault and web search all run in-cluster. Only egress: your model providers, which can be local.

One Helm chart

k3s and OrbStack for dev, EKS and GKE in the cloud, Talos Linux on bare metal for production.

Packages

Run it your way

A dedicated managed cluster on Crios Cloud, or the whole platform inside your perimeter with Crios Enterprise.

Dedicated clusters

Crios Cloud

Your own cluster, provisioned and operated by us, on a monthly subscription.

  • Dedicated bare-metal servers, never shared with another tenant
  • Capacity shown as parallel agent runs per workload profile
  • All five product lines included
  • Bring your own model keys, or use bundled routing
  • Provisioning, upgrades and TLS handled for you
  • Monthly billing, cancel any time, self-service renewal
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Crios Enterprise

The full platform, self-hosted and hardened for your organization.

  • Self-hosted on your Kubernetes, so data never leaves
  • Kata Containers microVM isolation, Vault secrets
  • Air-gap friendly: only egress is your model providers
  • Offline-verifiable license, no call-home required
  • Audit log webhook export, SSO, RBAC, per-project isolation
  • Deployment assistance, hardening review, SLA support
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Cloud & Enterprise

Talk to us

Tell us about your team and infrastructure, and we’ll get back to you at support@crios.ai.