Update content, pair down unused sections

Author: paulb-seldon

README.md

@@ -1,40 +1,47 @@
 <div align="center">
 
- <a href="https://www.seldon.io/">
+ <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, data-centric applications. With Core 2 you can deploy across a wide range of model types, on-prem or in any cloud, in a standardized way that is production-ready out of the box. 
+##  💡 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. 
 
-[![Introductory Youtube Video](./docs-gb/images/Core-intro-thumbnail.png)](https://www.youtube.com/watch?v=ar5lSG_idh4)
+</br>
+ <div align="center">
+   <a href="https://www.youtube.com/watch?v=ar5lSG_idh4">
+     <img src="./docs-gb/images/Core-intro-thumbnail.png" alt="Introductory Youtube Video" style="max-width: 100%; width: 500px; height: auto;">
+   </a>
+ </div>
+</br>
 
-## Features
+To learn more, or to contact Seldon regarding commercial use:
 
- * **Pipelines**: Deploy composable AI pipelines, leveraging Kafka for realtime data streaming between components
+👉 [Read the Documentation](https://docs.seldon.ai/seldon-core-2)  
+👉 [Contact Seldon](https://www.seldon.io/)
+
+ 
+## 🧩 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 pipeline, with support for A/B tests and shadow deployments
+ * **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!
 
-## Publication
-
-These features are influenced by our position paper on the next generation of ML model serving frameworks:
+## 🔬 Research
 
-*Title*: [Desiderata for next generation of ML model serving](http://arxiv.org/abs/2210.14665)
+These features are influenced by our position paper on the next generation of ML model serving frameworks: 
 
-*Workshop*: Challenges in deploying and monitoring ML systems workshop - NeurIPS 2022
+👉 [Desiderata for next generation of ML model serving](http://arxiv.org/abs/2210.14665)
 
+## 📜 License
 
-## ⚡️ Quickstart
-
+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.
 
-## Documentation
 
-[Seldon Core 2 docs](https://docs.seldon.ai/seldon-core-2)
 
-## 📜 License