Start with one flow.Scale to millions.
Durable orchestration for data, ML, and agents.
Trusted in Production by:
One platformfrom ML to AI
Data you can depend on
Replace brittle cron jobs with pipelines that heal themselves, so your data always arrives on time.
from prefect import flow, task@task(retries=3)def extract(source):...@flowdef daily_revenue_elt():load(transform(extract("warehouse")))
Teams ship faster on Prefect
From startups to enterprises, teams trust Prefect with the workflows their businesses depend on.
Annotate your code.
Add @flow to your Python functions for state, logging, and automatic retries. No new framework to learn.
@flow(retries=3)def process_data():data = extract()transform(data)load(data)
Our place or yours.
Run on managed compute, keep execution inside your own VPC, or anywhere in between. The same code deploys anywhere.
Runs you can trust.
Prefect executes your flows on your infrastructure, retries failures, scales out, and tracks every task, so runs recover on their own.
Back to building.
Skip building your own cron-and-Slack monitoring stack. One UI shows every run and flags what's late or failed, so you get your engineering hours back.
Never fly blind in production.
See every run across all your teams and infrastructure, and catch problems before they spread.
Open source at the core
Prefect Cloud runs on the open-source Prefect framework. We also build FastMCP, the open-source framework for building MCP servers that connect agents to your tools and data.
Questions answered
- What is Prefect?
- Prefect is a workflow orchestration platform for data, ML, and agents. You write workflows as plain Python, and Prefect runs them durably in production: scheduling, retries, caching, and recovery are part of the platform rather than code you maintain. The open-source framework and Prefect Cloud share the same core engine.
- Can my coding agent write Prefect workflows?
- Yes. A Prefect workflow is ordinary Python with two decorators, so any coding agent that writes Python can produce a working flow, add retries, and deploy it without learning a DSL. Your engineers review and own the result, and the same is true for humans: if you can write a Python function, you can ship a Prefect flow.
- How is Prefect different from Airflow?
- Three differences do most of the work. Workflows are plain Python functions that can branch, loop, and create tasks at runtime, rather than DAGs declared up front. Durable execution is built into the engine, so retries, state, and crash recovery are not code you write. And with Prefect Cloud there is no scheduler for your team to host, upgrade, or page anyone about.
- Do I have to run any infrastructure?
- Only if you want to. Prefect Serverless runs flows on managed compute, so you can start with zero infrastructure. Teams with stricter requirements use the hybrid model instead: lightweight workers inside your environment run your code where your data already lives, while the control plane handles scheduling and visibility. That split is what clears most security reviews.
- Is Prefect open source?
- Yes. The Prefect framework is open source under the Apache 2.0 license, and it is the same engine Prefect Cloud runs. Cloud adds the managed control plane, enterprise authentication, and scale on top; it does not fork the framework.
- What does the Dagster Labs acquisition mean for Prefect?
- Prefect acquired Dagster Labs in July 2026, bringing together two leading orchestration products. Nothing changes for users of either product: Dagster keeps its name and open-source license, and no action is required of any customer. The full announcement is at prefect.io/prefect-acquires-dagster.