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

# Token Allocation

<figure><img src="/files/TvjMmp2MtgIM946Kyazk" alt=""><figcaption></figcaption></figure>

**Initial Liquidity (30%):** SolAI recognizes the paramount importance of liquidity in fostering a vibrant and efficient marketplace. To ensure adequate liquidity from the outset, 30% of the total token supply is allocated to initial liquidity pools. These pools will facilitate seamless token trading and foster market depth, enhancing user experience and attracting liquidity providers.

**Minting (50%):** The minting phase plays a pivotal role in SolAI's token distribution strategy, comprising 50% of the total token allocation. Minting allows for the controlled release of tokens over time, providing flexibility in adjusting token supply according to market demand and project milestones. This allocation empowers the project to adapt to evolving market conditions while maintaining a balanced token ecosystem.

**Team Incentives (20% with three-month unlock):** SolAI recognizes the invaluable contributions of its team members to the project's success and longevity. To incentivize and retain top talent, 20% of the token supply is allocated to team members, subject to a three-month unlock period. This allocation ensures alignment of interests between the team and token holders, fostering long-term commitment and dedication to project development.

<br>


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://solvisionai.gitbook.io/solvisionai/solai-token/token-allocation.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.
