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Brief
Prefect

Prefect

Prefect enables data teams to build, run, and monitor resilient data workflows with a Python-native framework that emphasizes developer experience, dynamic pipeline generation, and comprehensive observability.

prefect.ioWashington, D.C., United StatesFounded 2018

Last updated May 11, 2026

Business Model
SaaS
Target Market
Enterprise and Mid-Market
Employee Count
51-200
Funding
$47M
API Available
Yes
Market Position

Leading modern workflow orchestration platform competing with Apache Airflow and other data pipeline tools

Overview

Prefect is a workflow orchestration and dataflow automation platform, not an AdTech company. It provides infrastructure for data engineers and data scientists to build, schedule, and monitor data pipelines and workflows. The platform offers both an open-source Python framework (Prefect Core) and a managed cloud service (Prefect Cloud) that adds enterprise features like authentication, authorization, and enhanced observability. Prefect competes in the modern data orchestration space alongside tools like Apache Airflow, Dagster, and Temporal. Prefect is not part of the advertising technology ecosystem. Instead, it serves the broader data engineering and MLOps markets, helping organizations automate complex data workflows, ETL processes, machine learning pipelines, and other data-intensive operations. The company has positioned itself as a more developer-friendly and flexible alternative to traditional workflow orchestration tools, emphasizing ease of use, dynamic workflow generation, and native Python integration.

Products & Features

Prefect Core

Open-source Python workflow orchestration framework for building and running data pipelines

Prefect Cloud

Managed cloud service providing orchestration, observability, and collaboration features for workflows

Prefect Server

Self-hosted backend for workflow orchestration with UI and API

Prefect Automations

Event-driven automation and alerting for workflow management

Key Features
Python-native workflow definitionDynamic workflow generationReal-time observability and monitoringAutomatic retries and error handlingDistributed executionEvent-driven automationsParameterized workflowsCaching and incremental processing
Use Cases
ETL and data pipeline orchestrationMachine learning workflow automationData warehouse managementBatch processing and scheduled jobsInfrastructure automationBusiness process automation
Customer Segments
Data EngineersData ScientistsMLOps TeamsAnalytics TeamsDevOps Engineers
Corporate history
  • 2018Founded
See integrations with Prefect (5)

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