FlowSynx Documentation

FlowSynx is an open automated fabric designed to orchestrate the flow of systems, data, and actions across an organization. It serves as a connective layer that allows teams to coordinate tasks across different platforms in a reliable, transparent, and scalable manner, bridging the gap between expensive custom integrations and rigid automation platforms.

FlowSynx is a cross-platform, .NET-based DAG (Directed Acyclic Graph) workflow orchestration system used to automate and manage complex data workflows. It allows developers to define declarative workflows using JSON, providing control over execution order, task dependencies, retries, error handling, and conditional logic. The system is designed for extensibility via a modular plugin architecture and a native C# SDK, supporting deployments across Windows, Linux, macOS, Docker, and Cloud environments.

FlowSynx is a lightweight, extensible, cross-platform orchestration engine built on .NET. It uses a modular micro-kernel design that separates orchestration logic from functional extensions, treating systems, datasets, and workflows as compositional substrates. It employs a plugin-driven, declarative Directed Acyclic Graph (DAG) architecture, allowing organizations to integrate legacy systems, cloud platforms, and modern applications.

FlowSynx is a centralized orchestration platform designed to manage complex, non-linear business workflows that span multiple teams, departments, and external partners. It integrates modern APIs, cloud services, databases, and legacy software into a unified system to reduce operational friction and manual errors.

FlowSynx is a plugin-driven, cross-platform .NET-based orchestration system used to automate and manage complex data workflows. It uses JSON-defined Directed Acyclic Graphs (DAGs) to control execution order, task dependencies, retries, error handling, and conditional logic. The system is designed to bridge low-code accessibility with full-code extensibility via a native C# SDK.

FlowSynx uses a modular plugin-based architecture to separate the core orchestration engine from functional capabilities. The core engine handles workflow execution, dependency resolution, and retries, while plugins provide the actionable logic such as tasks, triggers, connectors, and processors. This allows for extensibility without modifying the core system, reducing regression risk and preserving stability.

The Unified Data Abstraction Layer (UDAL) is a cohesive interface in FlowSynx that standardizes how data is accessed, transferred, transformed, validated, and synchronized across heterogeneous sources. It acts as an intermediary representation, normalizing raw data from various systems (files, APIs, databases) into a universal internal structure. This allows workflow tasks to operate on a predictable data model regardless of the physical source, reducing code duplication and decoupling workflow logic from specific storage technologies.

Get detailed information about a specific workflow using its unique identifier.

flowctl workflows details --workflow-id <workflow-id>

FlowSynx uses JSON Schema Validation as a contract and guardrail to ensure that workflow definitions (represented as Directed Acyclic Graphs or DAGs), task configurations, and plugin descriptors adhere to a strict, machine-verifiable structure. This prevents runtime errors by enforcing syntax correctness, type safety for inputs/outputs, and structural consistency across the workflow.