---
title: "Examples of Open Source Business Models"
source: The Turing Way
source_url: https://github.com/the-turing-way/the-turing-way
licence: CC-BY-4.0
domain: data-and-analysis
subdomain: turing-way
date_added: 2026-04-25
---

# Examples of Open Source Business Models

Open source has been an important theme for AI communities in academia and industry. 
Popular open source software libraries like [OpenCV](https://opencv.org/) and [Scikit-Learn](https://scikit-learn.org/), and open dataset and model providers like [Hugging Face](https://huggingface.co/) and [OpenAI](https://openai.com/) have shaped how AI algorithms are discovered, improved, shared, and deployed. 
While each organisation pursued different paths towards sustainability, reflective of when they were founded, some themes emerge around important initial steps.
 
## Community-led Sustainability Model
Of the four organisations of focus in this case study, OpenCV and Scikit-Learn started as community-driven projects. 
Both had a small group of motivated individuals with a mission of creating "optimised" and "accessible" code within their domains and found other interested supporters within their organisation or networks to help continue building out the project. 
These grassroots efforts served to generate interest among many across academia and industry and foster a sense of community among these different user groups. 
The Scikit-Learn community has recently spun out a company called [Probabl](https://techcrunch.com/2024/02/01/probabl-is-a-new-ai-company-built-around-popular-library-scikit-learn/), to offer services such as training and consulting relating to the scikit-learn codebase. 

## Investor-led Sustainability Model
In contrast, OpenAI and Hugging Face started as investor-funded organisations to tackle specific topics such as AI Safety and Chatbots. 
While Open AI began as a self-defined open source non-for-profit and Hugging Face as an AI product company, both have taken different paths as they have grown. 
After a private investment from Microsoft, Open AI split into a not-for-profit and for-profit arm. 
Around the same time, they also began exploring new models of releasing code and models in a more closed or tiered-access way, different from the original "open approach." 
In contrast, Hugging Face has moved in a different direction, transitioning from an AI product business model to become an open source AI model and data platform, with over 100,000 pre-trained models and 10,000 datasets hosted on the platform. 
It has also built [BigScience](https://bigscience.huggingface.co/), a multi-language Large Language Model (LLM) openly with collaborators around the world.

| Organisation | Founding Year | Founder & Founding Organisation | First Supporter(s) | Motivations |
| -------- | -------- | -------- | -------- | -------- |
| OpenCV     | 2000     | Gray Bradsky, Intel Engineer     | Intel researchers in Russia     | "...not only open but also optimized code for basic vision infrastructure. No more reinventing the wheel.""     |
| Scikit-Learn     | 2007     | David Cournapeau, Google Summer of Code     | Matthieu Brucher (thesis) & INRIA (French National Institute for Research in Digital Science and Technology)     | "designed to be simple and efficient, accessible to non-experts, and reusable in various contexts"     |
| OpenAI    | 2015     | $1B investment from Sam Altman and Elon Musk to tackle challenges around AGI     | $1B investment from Microsoft which led to capped-for-profit and not-for-profit division    | "We will attempt to directly build safe and beneficial AGI, but will also consider our mission fulfilled if our work aids others to achieve this outcome."     |
| Hugging Face     | 2016     | Clement Delangue and Julien Chaumond, Hugging Face chatbot apps     | VC funding     | "We think the direction of responsible AI is through openly sharing models, datasets, training procedures, eval metrics, and working together to solve issues"    |
