Kubiya
What is Kubiya?
Kubiya is an enterprise engineering automation platform for teams that turns loose requirements into governed execution across dev, staging, production, or on-prem environments. It combines Multi-Agent Orchestration, a Policy Engine, and Cognitive Memory, with integrations for Datadog, AWS, Slack, and Teams. Customers shown include A&E Networks, Atlassian, Microsoft, Ford, and Volkswagen. Plans run Professional at 2,500AEH annually and Enterprise with custom pricing.
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At a glance
- Kubiya is best for enterprise engineering teams who need governed AI execution across complex infrastructure.
- Professional 2,500AEH/annually; Enterprise CustomAEH
- 60 days, no credit card
- Yes — Kubiya says everything is programmable via API and lists REST API, GraphQL, Webhooks, and Event Streaming.
What does Kubiya do?
Kubiya turns engineering work into governed execution by combining a control plane, multi-agent orchestration, and a policy engine. It takes loose requirements, decomposes them into sub-tasks, and runs them across dev, staging, production, or on-prem environments with shared context and deterministic code paths. The platform's context graph pulls in signals from systems like Datadog and AWS, while Deep Context and Adaptive Recall help agents surface the right logs, incidents, and verified fixes instead of starting from scratch. At scale, Kubiya reports 2M+ automated tasks per month, $178M+ in engineering productivity gains, 4,459+ FTE equivalent capacity, and 99.9% uptime. It supports distributed LLM inferencing across open and proprietary models, and everything is programmable via REST API, GraphQL, Webhooks, and Event Streaming. Customers shown on the site include A&E Networks, Atlassian, Microsoft, Ford, and Volkswagen.
Why use Kubiya?
- Kubiya combines deterministic execution with context awareness, so teams can automate critical operations without relying on prompt-only behavior.
- Its self-hosted option lets organizations keep control of infrastructure when compliance or data-handling requirements are strict.
- The platform is built around a unified abstraction layer, reducing lock-in across models, runtimes, and deployment targets.
- Built-in analytics tie automation activity to ROI, AEH consumption, and engineering KPIs instead of leaving value hard to prove.
- Policy-driven governance and RBAC make it easier to operationalize AI in environments that need approvals, audit trails, and compliance enforcement.
Who is Kubiya for?
- Platform engineering teams who need AI workflows to run with policy controls and auditability.
- SRE and operations teams who want automated investigation and remediation across live systems.
- Engineering leaders who need measurable productivity gains from agentic automation.
- Security and compliance teams who require deterministic execution and controlled access.
- Developers who want to connect existing agents, scripts, and tools without rewriting them.
What are Kubiya's key features?
Production-Ready
Deploy production AI systems in under 30 minutes with 99.9% uptime, so engineering teams can automate work without adding fragile one-off scripts.
Enterprise-Grade Security
Use RBAC, audit trails, SSO, social login, and custom SLA/compliance controls to keep agent actions governed in regulated environments.
Virtual Team
Create agents that set goals, plan, approve, execute, and remember context, giving teams a repeatable way to delegate operational work.
Any API / Tool
Connect agents to Slack, Teams, REST, GraphQL, Webhooks, Event Streaming, Datadog, and AWS to act across existing systems.
Multi-Agent Orchestration
Run alert-triggered investigations where agents query logs, metrics, and deployment history, then suggest fixes or escalate to humans.
Cognitive Memory
Store deep context and adaptive recall across tasks, helping agents keep prior decisions and investigation history available for later actions.
Policy Engine
Apply Open Policy Agent controls to agent workflows, so approvals and execution rules stay consistent across teams and environments.
One Platform. Any Model. Any Runtime.
Choose OpenAI, Anthropic, Llama, or Mistral models and run agents in your cluster with self-hosting support for deployment flexibility.
What does Kubiya integrate with?
- Slack
- REST
- GraphQL
- Webhooks
- Event Streaming
- Microsoft Teams
- Datadog
- AWS
- OpenAI
- Anthropic
- Llama
- Mistral
- Open Policy Agent
What are Kubiya's use cases?
SRE incident investigation
SRE and operations teams use Kubiya to investigate live incidents faster, using Multi-Agent Orchestration to pull logs, metrics, and deployment history into one root-cause workflow. They can then use Execution to push a fix or escalate with a clear audit trail.
Policy-controlled platform automation
Platform engineering teams use Kubiya to run AI workflows with guardrails, using Policy Engine and Approval to keep actions deterministic and compliant. That lets them automate routine engineering tasks without losing control over who can do what.
Developer tool integration
Developers use Kubiya to connect existing scripts, agents, and internal tools without rewriting them, using Any API / Tool and API-First Architecture to wire everything into one workflow. They can ship agentic automations faster while keeping their current stack intact.
Measurable productivity gains
Engineering leaders use Kubiya to turn automation into measurable output, using Virtual Team and Track & Collaborate to monitor work across agents and humans. That makes it easier to show productivity gains, capacity unlocked, and where automation is actually paying off.
How does Kubiya work?
- Trigger a multi-agent investigation from an alert or event, then let Kubiya start the first workflow automatically.
- Have agents query logs, metrics, and deployment history through connected systems, using the API-First Architecture and Any API / Tool support.
- Review the root-cause analysis and suggested fixes in the Control Plane, with Memory preserving context across repeated incidents.
- Approve automated remediation or escalate to humans, using Policy Engine and Approval to keep every action controlled and auditable.
How much does Kubiya cost?
Professional
2,500AEH/annually- For growing engineering teams
- Yearly commitment required
- Full platform access
- Unlimited agents
- Limited Hosted Multi-Tenancy Context Graph
- Support
- Custom integrations
- RBAC & audit trail
- SSO & social login
Enterprise
CustomAEH- Custom solutions for large organizations
- Contact sales for pricing
- Everything in Professional
- Forward Deployed Engineer services
- Dedicated Context Graph(Optional)
- Dedicated support team
- Run agents in your cluster
- Bring your own LLM
- Custom SLA & compliance
Frequently asked questions
What is Kubiya?
Kubiya is an enterprise engineering automation platform for teams that turns loose requirements into governed execution across dev, staging, production, or on-prem environments. It combines Multi-Agent Orchestration, a Policy Engine, and Cognitive Memory, with integrations for Datadog, AWS, Slack, and Teams. Customers shown include A&E Networks, Atlassian, Microsoft, Ford, and Volkswagen. Plans run Professional at 2,500AEH annually and Enterprise with custom pricing.
How much does Kubiya cost? Is it free?
Kubiya has 2 paid plans: Professional at 2,500AEH/annually, Enterprise at CustomAEH. A 60-day free trial is available.
What is Kubiya used for? Who is it for?
Kubiya is used for Production-Ready, Enterprise-Grade Security, and Virtual Team. It's built for Platform engineering teams, SRE and operations teams, and Engineering leaders.
Does Kubiya have an API and what does it integrate with?
Kubiya says everything is programmable via API and lists REST API, GraphQL, Webhooks, and Event Streaming. It integrates with Slack, REST, GraphQL, Webhooks, Event Streaming, and 8 more.
Editor's read
Check whether the Professional plan's limited Hosted Multi-Tenancy Context Graph is enough for your workflows. If you need agents to run in your own cluster, bring your own LLM, or require custom SLA and compliance controls, that is listed under Enterprise.
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