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Prefect

Workflow orchestration framework for data and ML pipelines

AI InfrastructureFounded 2018#16 of 55 in AI Infrastructure

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Company research

Current company data

No company research card is published for Prefect yet. The current company data below lists package, repository, and discussion metrics AI-Buzz can inspect today; AI-Buzz publishes a card when recent public metrics show a measured change with dated evidence and cited sources.

Package downloads (30d)

11.3M/30d

Dependent projects

363

dependents · latest

GitHub stars

23.3K

Hacker News

6/30d

Note: Public metrics are incomplete, and current data alone does not prove a trend; they do not show private usage, paid use, customer count, or product quality.

Company profile

What is Prefect?

Prefect provides an open-source workflow orchestration framework that helps data engineers and scientists build, run, and monitor complex data and machine learning pipelines. It aims to make dataflow reliable by offering tools for scheduling, logging, retries, and error handling, significantly improving the robustness and observability of MLOps workflows.

Latest company data

Metric dates vary by source

Metric dates
PyPI downloads
PyPI dependents
GitHub stars
Hacker News mentions

Key metric

Package downloads (30d)

11.3M/30d

Tracked package: PyPI prefect

▼ -24%

Additional metrics

3 metrics

Metric

Dependent projects

363

Projects depending on tracked package: PyPI prefect

Metric

GitHub stars

23.3K

Main repository stars

Metric

Hacker News

6/30d

Position #30 in category discussion

Repository health

Maintenance data from the main open-source repository.

OpenSSF Scorecard
6.9
Key-person risk
1
External contributors
55
% of recent contributors outside the core team
Releases (30d)
0

Repository usage

Public repositories and source files importing packages tied to Prefect.

Repos importing
7670%

About Prefect

Prefect provides an open-source workflow orchestration framework that helps data engineers and scientists build, run, and monitor complex data and machine learning pipelines. It aims to make dataflow reliable by offering tools for scheduling, logging, retries, and error handling, significantly improving the robustness and observability of MLOps workflows.

FoundersJeremiah Lowin, Chris White

Disclosed funding

Disclosed $46M · 3 rounds

Disclosed funding records total $46M. Category position #16 of 55 in AI Infrastructure.

Series B2021

Tiger Global

$32M
Series A2021

Positive Sum

$12M
Seed2019

Harrison Metal

$3M

Investors

Harrison MetalPositive SumTiger Global

Tracked packages (1)

1 PyPI

prefect

PyPIMain PyPI package

prefect

Workflow orchestration framework for data and ML pipelines