> For the complete documentation index, see [llms.txt](https://syneriss-organization.gitbook.io/syneris/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://syneriss-organization.gitbook.io/syneris/mission.md).

# Mission

To achieve this, Syneris will initially build a shared GPU and CPU network while integrating the existing GPU resources from other protocols and we are actively working to update the list of partners in the project’s roadmap

This strategic approach enables the sharing of computational processing power across the combined networks, enhancing data processing capabilities and maximizing cost efficiency. During these foundational stages, we will leverage our GPU network alongside IO.NET's resources to establish a robust network capable of supporting AI model deployment and expediting subsequent goals.

As we progress, our commitment to developing our own network will reduce our reliance on third-party GPU networks. This strategy is crucial for lowering operational costs associated with running AI models on our platform. By emphasizing this approach, we ensure the feasibility of our project, allowing for rapid development and execution of AI models without the constraints of waiting for our network to scale sufficiently. As our network grows and matures, it will become increasingly self-sufficient, maximizing cost savings and unlocking new opportunities for innovation.

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