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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
An MLOps framework to package, deploy, monitor and manage thousands of production machine learning models
| Date | Stars |
|---|---|
| 2026-07-31 | 4765 |
| 2026-08-01 | 4765 |
| 2026-08-02 | 4765 |
| 2026-08-06 | 4765 |
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growth rate 0.00%/day
<div align="center">
<a href="https://www.seldon.io/solutions/core/">
<img alt="Core 2 Logo" src="/.images/core-2-logo.png" alt="Core 2 Logo" style="max-width: 100%; height: auto; width: 400px;">
</a>
</div>
# Deploy Modular, Data-centric AI applications at scale
## 💡 About
Seldon Core 2 is an MLOps and LLMOps framework for deploying, managing and scaling AI systems in Kubernetes - from singular models, to modular and data-centric applications. With Core 2 you can deploy in a standardized way across a wide range of model types, on-prem or in any cloud, and production-ready out of the box.
</br>
<div align="center">
<a href="https://www.youtube.com/watch?v=ar5lSG_idh4">
<img src="/.images/Core-intro-thumbnail.png" alt="Introductory Youtube Video" style="max-width: 100%; width: 500px; height: auto;">
</a>
</div>
</br>
To reach out to Seldon regarding commercial use, visit our [website](https://www.seldon.io/).
## 📚 Documentation
The Seldon Core 2 Docs can be found [here](https://docs.seldon.ai/seldon-core-2). For most specific sections, see here:
<p align="center">
<a href="https://docs.seldon.ai/seldon-core-2/installation/installation">🔧 Installation</a>   •  
<a href="https://docs.seldon.ai/seldon-core-2/user-guide/servers"> ⛽ Servers</a>   •  
<a href="https://docs.seldon.ai/seldon-core-2/user-guide/models">🤖 Models</a>   •  
<a href="https://docs.seldon.ai/seldon-core-2/user-guide/pipelines"> 🔗 Pipelines</a>   •  
<a href="https://docs.seldon.ai/seldon-core-2/user-guide/experiment">🧑🔬 Experiments</a>   •  
<a href="https://docs.seldon.ai/seldon-core-2/user-guide/performance-tuning">📊 Performance Tuning</a>
</p>
## 🧩 Features
* **Pipelines**: Deploy composable AI applications, leveraging Kafka for realtime data streaming between components
* **Autoscaling** for models and application components based on native or custom logic
* **Multi-Model Serving**: Save infrastructure costs by consolidating multiple models on shared inference servers
* **Overcommit**: Deploy more models than available memory allows, saving infrastructure costs for unused models
* **Experiments**: Route data between candidate models or pipelines, with support for A/B tests and shadow deployments
* **Custom Components**: Implement custom logic, drift & outlier detection, LLMs and more through plug-and-play integrate with the rest of Seldon's ecosytem of ML/AI products!
## 🔬 Research
These features are influenced by our position paper on the next generation of ML model serving frameworks:
👉 [Desiderata for next generation of ML model serving](http://arxiv.org/abs/2210.14665)
## 📜 License
Seldon is distributed under the terms of the The Business Source License. A complete version of the license is available in the [LICENSE file](LICENSE) in this repository. Any contribution made to this project will be licensed under the Business Source License.
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:aaa5b227c99eac2e, topic:mlops, topic:machine-learning-operations, desc:mlops