Update README.md (#2345)

Author: savingoyal

README.md

@@ -4,7 +4,7 @@
 
 [Metaflow](https://metaflow.org) is a human-centric framework designed to help scientists and engineers **build and manage real-life AI and ML systems**. Serving teams of all sizes and scale, Metaflow streamlines the entire development lifecycle—from rapid prototyping in notebooks to reliable, maintainable production deployments—enabling teams to iterate quickly and deliver robust systems efficiently.
 
-Originally developed at [Netflix](https://netflixtechblog.com/open-sourcing-metaflow-a-human-centric-framework-for-data-science-fa72e04a5d9), Metaflow is designed to boost the productivity for research and engineering teams working on [a wide variety of projects](https://netflixtechblog.com/supporting-diverse-ml-systems-at-netflix-2d2e6b6d205d), from classical statistics to state-of-the-art deep learning and foundation models. By unifying code, data, and compute at every stage, Metaflow ensures seamless, end-to-end management of real-world AI and ML systems.
+Originally developed at [Netflix](https://netflixtechblog.com/open-sourcing-metaflow-a-human-centric-framework-for-data-science-fa72e04a5d9) and now supported by [Outerbounds](https://outerbounds.com), Metaflow is designed to boost the productivity for research and engineering teams working on [a wide variety of projects](https://netflixtechblog.com/supporting-diverse-ml-systems-at-netflix-2d2e6b6d205d), from classical statistics to state-of-the-art deep learning and foundation models. By unifying code, data, and compute at every stage, Metaflow ensures seamless, end-to-end management of real-world AI and ML systems.
 
 Today, Metaflow powers thousands of AI and ML experiences across a diverse array of companies, large and small, including Amazon, Doordash, Dyson, Goldman Sachs, Ramp, and [many others](ADOPTERS.md). At Netflix alone, Metaflow supports over 3000 AI and ML projects, executes hundreds of millions of data-intensive high-performance compute jobs processing petabytes of data and manages tens of petabytes of models and artifacts for hundreds of users across its AI, ML, data science, and engineering teams.