> For the complete documentation index, see [llms.txt](https://skillful-ai.gitbook.io/skillful-ai-public-docs/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://skillful-ai.gitbook.io/skillful-ai-public-docs/skillfulai_docs_v1.0/ecosystem-overview.md).

# Ecosystem Overview

The Skillful AI ecosystem is designed to create an adaptable framework for AI model training, personalization, and deployment.

Using industry-leading datasets, we combines flexibility and innovation to build AI models that evolve into specialized tools for different applications. 

Our tech stack ecosystem also ensures compatibility with new developments including new LLMs while maintaining a strong foundation of our in-house models and tools.

<figure><img src="/files/81RztwWQekg3ieLdPFdw" alt=""><figcaption><p>Skillful AI Tech Stack</p></figcaption></figure>

<figure><img src="/files/g2C6T8Y0U77KpXSAGVsb" alt=""><figcaption><p>Skillful Ecosystem</p></figcaption></figure>

### Tr**aining Models**

At the heart of the ecosystem are Training Models, which use data from existing LLMs as a starting point.&#x20;

These models are fine-tuned/refined to specialize in various fields, making them very effective for specific applications. This allows for:

* **Continuous Integration:** New advancements in AI (i.e., new LLMs) can be incorporated easily in our platform without disrupting existing workflows.
* **Adaptable Development:** Models evolve to meet the demands of emerging fields while retaining flexibility for further customization.

For Example, a Medical Diagnosis Model starts as a general LLM but is refined with comprehensive medical datasets to recognize symptom patterns and recommend diagnoses. Similarly, a Legal Research Model could help lawyers search case laws and provide context-specific insights.

### **Personal Models (Coming Soon)**

We also provide users with the ability to create Personal Models tailored to their specific needs. This is offered through three key methods:

* **User Interaction:** Users can train personal models by engaging directly with Training Models.&#x20;
  * A content creator could train a model based on their unique writing style and generate articles or social media posts accordingly.&#x20;
* **Model Library:** Pre-built models from our curated library provide quick and reliable solutions.&#x20;
  * A small business owner could use a Marketing Analytics Model from the library to track and optimize ad campaigns.
* **Custom Developer Training**: Developers can personalize base models using specific datasets or interactions, enabling them to sell these models on the AI marketplace.&#x20;
  * A game developer trains a base model for generating dynamic NPC dialogues in video games, then offers it for sale to other developers.

For a more comprehensive understanding of the ecosystem's functionality, please refer to our [Whitepaper.](https://drive.google.com/file/d/1QrR7I3-3k_WyUwVbfOMP0PT9_0LCFCuU/view)