> ## Documentation Index
> Fetch the complete documentation index at: https://docs.agno.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Parallel Workflow

> Run independent steps concurrently with Parallel and pass their combined output to the next step.

**Example use cases**: Multi-source research, parallel analysis, concurrent data processing

Steps inside a `Parallel` block run concurrently. Their outputs are aggregated in the configured step order and passed to the next step in the workflow.

<img className="block dark:hidden" src="https://mintcdn.com/agno-v2/JYIBgMrzFEujZh3_/images/workflows-parallel-steps-light.png?fit=max&auto=format&n=JYIBgMrzFEujZh3_&q=85&s=afda5268ab0637c6064ace8edd6f35e5" alt="Workflows parallel steps diagram" width="3441" height="756" data-path="images/workflows-parallel-steps-light.png" />

<img className="hidden dark:block" src="https://mintcdn.com/agno-v2/JYIBgMrzFEujZh3_/images/workflows-parallel-steps.png?fit=max&auto=format&n=JYIBgMrzFEujZh3_&q=85&s=ec4f6c7c9a6ef76cec8f0866eb1acc5b" alt="Workflows parallel steps diagram" width="3441" height="756" data-path="images/workflows-parallel-steps.png" />

## Example

```python parallel_workflow.py theme={null}
from agno.workflow import Parallel, Step, StepInput, StepOutput, Workflow


def research_hackernews(step_input: StepInput) -> StepOutput:
    return StepOutput(content=f"HackerNews notes for {step_input.input}")


def research_web(step_input: StepInput) -> StepOutput:
    return StepOutput(content=f"Web notes for {step_input.input}")


def research_papers(step_input: StepInput) -> StepOutput:
    return StepOutput(content=f"Paper notes for {step_input.input}")


def synthesize(step_input: StepInput) -> StepOutput:
    combined = step_input.previous_step_content or "No research returned"
    return StepOutput(content=f"Synthesis:\n{combined}")

workflow = Workflow(
    name="Parallel Research Pipeline",
    steps=[
        Parallel(
            Step(name="HackerNews Research", executor=research_hackernews),
            Step(name="Web Research", executor=research_web),
            Step(name="Academic Research", executor=research_papers),
            name="Research Step",
        ),
        Step(name="Synthesis", executor=synthesize),
    ],
)

workflow.print_response("Write about the latest AI developments", markdown=True)
```

## Handling Session State Data in Parallel Steps

Custom Python functions can accept a `run_context` parameter and update `run_context.session_state`.

Parallel branches share that session-state dictionary. Coordinate writes to the same keys, or assign separate keys to each branch, to avoid races.

## Developer Resources

* [Parallel Steps Workflow](/workflows/usage/parallel-steps-workflow)
* [Session State in a Function](/examples/workflows/advanced-concepts/session-state/state-in-function)

## Reference

For complete API documentation, see [Parallel Steps Reference](/reference/workflows/parallel-steps).