Kubiya Platform Overview

Kubiya is a comprehensive platform for building, deploying, and managing AI-powered automation workflows.

Core Components

Workflow Engine

Deterministic workflow execution with support for complex DAGs, parallel execution, and error handling

AI Integration

Native AI capabilities through providers like ADK for intelligent automation

Runner Infrastructure

Distributed execution across self-hosted or Kubiya-managed runners

Tool Ecosystem

Extensive library of pre-built tools and integrations

Architecture

Key Features

πŸ”„ Deterministic Execution

Unlike traditional AI agents, Kubiya workflows are deterministic and predictable, making them suitable for production environments.

πŸš€ Scalable Infrastructure

Deploy runners in your own infrastructure or use Kubiya-hosted runners for instant scalability.

πŸ€– AI-Powered Automation

Combine deterministic workflows with AI capabilities for intelligent decision-making and natural language interfaces.

πŸ”Œ Extensive Integrations

Connect to your existing tools and services through pre-built integrations or custom tools.

Platform Capabilities

Workflow Management

  • Visual workflow designer
  • Version control and rollback
  • Audit logging and compliance
  • Schedule and trigger management

Security & Compliance

  • Role-based access control (RBAC)
  • Secrets management
  • Audit trails
  • SOC2 compliance

Monitoring & Observability

  • Real-time execution tracking
  • Performance metrics
  • Error tracking and alerts
  • Custom dashboards

Developer Experience

  • Comprehensive SDK
  • CLI tools
  • API-first design
  • Local development environment

Getting Started

1

Install the SDK

pip install kubiya-workflow-sdk
2

Create Your First Workflow

from kubiya_workflow_sdk.dsl import workflow

wf = workflow("hello-kubiya").step("greet", "echo 'Hello, Kubiya!'")
3

Deploy and Execute

from kubiya_workflow_sdk import execute_workflow

result = execute_workflow(wf.to_dict(), api_key="YOUR_KEY")

Next Steps