Skip to content

Agentic Workflow Engine

Orkes Conductor is the enterprise platform for Conductor OSS, available fully managed or in your own environment — the durable workflow engine that executes an AI agent's real business work — tool calls, side effects, and multi-step actions.

Use it when an agent has to execute real work, not only generate a response.

Agent frameworks can still own reasoning, prompts, planning, and model-specific loops. Conductor owns the execution path: persisted state, task queues, retries, timeouts, durable waits, tool routing, human approval, compensation, replay, governance, and audit history.

Conductor OSS is the durable workflow engine with a built-in agent runtime. Orkes Conductor is the enterprise platform built on it, available as a fully managed cloud or deployed in your own environment.

What changes in production

Production need What Conductor provides
The agent process crashes Completed steps remain persisted and execution resumes from the next incomplete task.
A tool call times out Only the failed task retries. Prior model calls and completed tool outputs are preserved.
A human review takes days The workflow waits without holding a process, thread, or in-memory session.
A tool has side effects Idempotency keys, retry policies, and compensation workflows keep side effects controlled.
Operators need proof Every task records inputs, outputs, timing, retry count, logs, and status history.
Teams need governance Access control, secrets, applications, tags, schedules, webhooks, and gateways are part of the platform.

The production boundary

Keep in the agent framework Move into Conductor
Reasoning and planning Durable workflow state
Prompt and memory strategy Task queues and worker routing
Model-specific loops Retries, timeouts, and rate limits
Tool choice Auditable tool execution
Local graph composition Human approvals, timers, callbacks, and compensation

This boundary keeps the agent flexible while making the work recoverable. The model can decide what should happen next; Conductor makes sure selected work is executed, recovered, and observable.

Build paths

Why workflows are code-native, not JSON-only

Conductor workflow definitions describe orchestration. Workers and services hold your business logic. You can write workers in Python, Java, Go, .NET/C#, Ruby, Rust, TypeScript, or any service that can poll the task API.

Use JSON where the runtime needs a stable, inspectable, versioned execution graph. Use code where application logic belongs. This is how Conductor handles complex workflows without forcing every decision into static JSON.

Prove it before rollout

Before moving an agent workflow into production, run these checks:

  1. Kill a worker after an LLM task completes and confirm the LLM task is not repeated.
  2. Force a tool timeout and confirm only the failed tool task retries.
  3. Leave a human task open across a deploy and confirm the workflow resumes when approved.
  4. Retry a side-effecting task with the same idempotency key and confirm duplicate work is prevented or compensated.
  5. Inspect the execution history and confirm operators can see inputs, outputs, timing, retry counts, and failure reasons.