Orkes

Drag-and-drop workflow builder that allows users to visually compose multi-step processes without writing code. Provides a graphical interface for connecting tasks, defining branching logic, and configuring workflow parameters.

Coordinates execution of distributed microservices and tasks across multiple systems in a defined sequence or pattern. Manages task dependencies, parallel execution, and ensures deterministic ordering of operations.

Executes multiple tasks concurrently within a workflow and synchronizes their completion. Reduces overall workflow execution time by running independent tasks in parallel.

Allows developers to create custom task types and integrate arbitrary code or external services into workflows. Provides SDKs and APIs for extending the platform with custom logic.

Maps and transforms data between workflow steps, handling input/output serialization and data transformation. Allows passing data through the workflow with variable substitution and transformation.

Leverages the open-source Conductor orchestration engine, avoiding vendor lock-in and enabling self-hosted deployments. Provides access to the underlying engine for customization and control.

Provides a free tier with generous limits that supports real production workloads without requiring immediate paid upgrades. Enables small teams and startups to run production workflows at no cost.

Automatically retries failed tasks with configurable backoff strategies and handles errors gracefully without manual intervention. Provides built-in mechanisms for exponential backoff, max retry counts, and error recovery paths.

Pauses workflow execution and routes tasks to humans for review, approval, or manual intervention before continuing. Enables workflows that require human decision-making at specific checkpoints.

Natively integrates Large Language Models and AI services into workflows with built-in prompt management and token counting. Allows workflows to leverage AI capabilities without external wrapper code.

Stores, versions, and manages prompt templates used in AI-integrated workflows. Provides centralized control over prompts with variable substitution and version history.

Monitors and reports token consumption across LLM calls within workflows. Provides visibility into API costs and usage patterns for budget management.

Provides real-time visibility into workflow execution status, task progress, and performance metrics. Tracks execution history and provides debugging information for failed workflows.

Manages multiple versions of workflows and controls deployment across environments. Enables safe rollback and A/B testing of workflow changes.

Routes workflow execution along different paths based on conditions and decision logic. Supports complex branching scenarios including if-then-else, switch statements, and dynamic routing.