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

# Roadmap

#### Phase 1: Project Initiation and Infrastructure Development

* Token Launch
* Introducing GPU infrastructure: To improve AI processing capacity, introduce GPU-accelerated computing capabilities.
* Creating AI agents: Use AI agents to help AI models make intelligent decisions and behave adaptively.
* Integration of the AI Layer1 DAG blockchain: To build a highly scalable and effective blockchain for AI applications, introduce the AI Layer1 DAG blockchain, which combines components of BitTensor and KASPA.
* Deployment of decentralized AI nodes: To enable GPU-accelerated computation and AI agents, extend the network of distributed AI nodes.

#### Phase 2: Platform Expansion and Integrations

* AI marketplace launch: Create a marketplace for developers to utilize, commercialize, and distribute AI models and algorithms to consumers.
* AI-as-a-Service (AIaaS): Provide users with AI-as-a-Service options so they are able to pay for the resources used and get AI capabilities whenever they need them.
* Increased usage cases: Examine novel decentralized AI application cases in sectors, such as finance, healthcare, and smart cities.
* Improved compatibility: Boost communication between internal and external networks and systems to provide easy integration with current cloud infrastructure and AI frameworks.

#### Phase 3: Community Building and Engagement

* Community-driven governance: Put in place decentralized governance systems to enable stakeholders to take part in the formulation and application of AI-related policies.
* Outreach to developers and support: Offer information, guidelines, and assistance to developers that want to use the DeCloud platform to create AI applications.
* Education and awareness campaigns: Start educational programs to inform users and developers about the possibilities of cloud computing and decentralized AI and building on DeCloud.
* Strategic partnerships: To promote development and innovation in the decentralized AI and cloud computing area, create alliances and partnerships with other initiatives and platforms.

#### Phase 4: Scaling and Optimization

* Infrastructure scalability: To meet rising demand and workload needs, expand GPU infrastructure and decentralized AI nodes.
* Algorithm optimization: To increase accuracy, efficiency, and performance, AI algorithms and models should be continuously improved.
* Research & development: Make investments in this area to investigate novel AI methods, tools, and uses.
* Iterate and enhance the DeCloud platform continuously, taking into account user input, industry trends, and technology improvements.