The c10r workflow engine lets you design multi-step processes visually. Drag nodes onto a canvas, connect them with edges, and deploy pipelines that coordinate AI agents, API calls, conditional logic, and human approval steps.
Every workflow is a directed graph of nodes. Triggers start execution, actions perform work, conditions control flow, and AI nodes bring intelligence to every step.
Entry points that initiate workflow execution based on events, schedules, or external signals.
Execution primitives that perform work -- send messages, modify data, invoke external services.
Flow control primitives that split execution paths based on data conditions and expressions.
Invoke AI agents as workflow steps for classification, generation, extraction, or decision-making.
Full visibility into every run. Inspect node-by-node results, debug failures, and replay executions.
Connect to any external system through webhooks, HTTP actions, and custom code execution.
The c10r canvas editor provides a node-and-edge interface for building workflows. Drag nodes from the library, connect outputs to inputs, configure each step through structured forms, and deploy with a single click.
c10r workflows support parallel execution natively. Split a pipeline into concurrent branches that run simultaneously, then merge results at a synchronization point. This is essential for workflows that need to query multiple systems, notify multiple channels, or coordinate multiple agents at once.
These patterns represent proven approaches to orchestrating agents, data flows, and human decision points within c10r workflows.
Sequential agent execution where each agent's output becomes the next agent's input. Ideal for multi-stage processing like classify, enrich, then act.
Pause pipeline execution at critical decision points and wait for human approval before proceeding. Combines AI speed with human judgment.
Fan out a single event to multiple delivery channels simultaneously -- email, SMS, Telegram, webhook -- with channel-specific formatting.
Extract data from external sources, transform it using AI agents, load enriched records into your system. Scheduled or event-driven.
Every record passes through an AI compliance check before being committed. Flag violations, require approval for edge cases, auto-approve clean data.
Try automated resolution first. If unresolved after N minutes, escalate to next tier. Built-in timeout handling and fallback paths.
Open the canvas editor, drag your first nodes, and deploy a workflow that runs 24/7. No code required, no infrastructure to manage.