
Flyte | One Platform for Your AI Orchestration Needs
Flyte 2 is available today locally. For distributed execution, try Flyte 1. Agents AI Data
Flyte - User guide | Union.ai Docs
Flyte is a free and open source platform that provides a full suite of powerful features for orchestrating AI workflows. Flyte empowers AI development teams to rapidly ship high-quality code to production by …
Platform - Flyte
Flyte lets you write code in any language using raw containers, or choose Python, Java, Scala or JavaScript SDKs to develop your Flyte workflows. You can use the languages you are most …
Introduction to Flyte
Introduction to Flyte # Flyte is a workflow orchestrator that unifies machine learning, data engineering, and data analytics stacks for building robust and reliable applications.
User guide — Flyte
This User guide, the Tutorials and the Integrations examples cover all of the key features of Flyte for data analytics, data science and machine learning practitioners, organized by topic.
Welcome to Flyte! — Flyte
Flyte is an open-source, Kubernetes-native workflow orchestrator implemented in Go. It enables highly concurrent, scalable and reproducible workflows for data processing, machine learning and analytics.
Flyte 2 Is Here: Open-Source AI Orchestration Is Now Available Locally
6 days ago · Flyte 2 delivers fully dynamic workflows that adapt in real time. From branching logic and loops to dynamic resource allocation, your AI systems and agents can make decisions on the fly at …
Flyte #announcements
Today Flyte is used by some of the largest companies in the world to build and deliver their compound AI products. Recently, we decided to make a change, move Flyte docs to the same platform where …
Resources - Flyte
Introducing Union.ai The enterprise Flyte platform Orchestrate, ship, and scale AI systems from experiment to production. Union.ai’s platform accelerates teams through AI orchestration, training, …
Running a workflow locally — Flyte
In a local Python environment: To develop and test your code quickly without the overhead of setting up a local Flyte cluster, you can run your workflow in your local Python environment.