Kubiya.ai - Product & Platform
kubiya
Kubiya.ai - Product & Platform
Core Technology / Architecture
Multi-layered orchestration system:
- Control Plane -- Coordination hub managing routing, shared config, and policy enforcement. SaaS or self-hosted.
- Distributed Task Workers -- Execute workloads in isolated MicroVM containers with streaming logs and full audit trails.
- Context Graph ("The Brain") -- Vector-database-backed system ingesting data from Slack, docs, code repos, cloud providers, and identity systems to build a living map of tribal knowledge and infrastructure topology.
- Governance & Policy Layer -- OPA-based guardrails with RBAC/ABAC, compliance enforcement, Policy-as-Code.
- Unified API Layer -- REST, GraphQL, webhooks, event streaming.
- Multi-Model Orchestration -- Supports 100+ LLM providers via LiteLLM. Automatic failover and cost optimization.
Key Architectural Principles
- 100% Deterministic Execution -- Agents follow strictly defined code paths. No hallucination-driven actions on production infrastructure.
- Zero Vendor Lock-in -- Works with any agent framework, any container registry, any cloud provider.
- Zero Trust Security -- Task-level isolation, least-privilege credential scoping, complete I/O logging.
Key Features
| Feature | Description |
|---|---|
| AI Teammates / Virtual Team | Customizable roles (Manager, Dev, Security, Ops) defined as code |
| Meta Agent | Primary orchestration interface coordinating specialized agents |
| Domain-Specific Agents | Terraform, GitHub, Shell, PagerDuty, Jira, Kubernetes, etc. |
| Natural Language Interface | Plain English via Slack, Teams, or CLI |
| Context Graph | Adaptive recall of logs, past incidents, verified solutions, infra topology |
| Task Kanban | Real-time board tracking Pending/Running/Waiting/Completed/Failed |
| Human-in-the-Loop Approvals | Embedded approve/deny control points |
| Goal Setting & ROI Tracking | Define success metrics and measure engineering productivity |
| Cognitive Memory | Agents learn from execution history; shared across team |
| Connectors | Pre-built: AWS, GitHub, Jira, Slack, Kubernetes, Terraform, CI/CD, custom APIs |
| MCP Support | Model Context Protocol for standardized tool integration |
| Enterprise Security | SOC 2 Type II, GDPR, CCPA; HIPAA-ready for self-hosted; air-gapped support |
How It Works (6 Steps)
- Sign in at compose.kubiya.ai and launch the Meta Agent
- Connect services (AWS, GitHub, Jira, Slack, K8s) via Connectors
- Ingest data sources to populate the Context Graph
- Query infrastructure through natural language
- Execute tasks via Task Queues with isolated MicroVM execution
- Scale with specialized agents and teams
Deployment Options
- SaaS (Kubiya-hosted)
- Self-Hosted (private infrastructure)
- Air-Gapped (fully isolated)
Pricing
AEH (Agentic Engineering Hours) retainer model with yearly commitments:
| Plan | Cost | Key Features |
|---|---|---|
| Professional | 2,500 AEH/year | Full platform, unlimited agents, hosted Context Graph, SSO |
| Enterprise | Custom | + Forward Deployed Engineer, BYO LLM, dedicated support, run in your cluster |
2-month pilot program available, converting to yearly agreement upon success.
Impact Metrics (Customer-Reported)
- 70% reduction in MTTR
- 300% decrease in time to production
- 20x increase in deployment speed
- 120 hours gained per engineer per month
- Developer SLAs: 3 days to 1 hour (Verana Health)