# Wide Application Scenarios Developers are the cornerstone of Adot. Developers can implement tools available in the Adot ecosystem to acquire and composite the data by their own demands and support their applications, including but not limited to the following application scenarios. ## Social By parsing social user identities and aggregating social data, Adot is capable of generating relationship graphs and knowledge networks based on blockchain wallet addresses, helping Web3 social applications build powerful search capabilities and complete datasets. ## Aggregation Adot aggregates related information to enrich the reference content regarding tokenized assets, which will help traders to browse and trade assets, and potentially enhance the value of assets. ## Publishing Adot aims to create a more effective content distribution channel to empower the creator economy. Adot breaks down the walls across applications and protocols and improves the traditional sorting algorithm that aims to distribute high-quality content to more targeted audiences and therefore bring creators exponential traffic and even royalty income. ## Analysis As introduced, Adot indexes a high and diverse coverage of data sources, which makes it a powerful reference regarding the analytics purpose. From analyzing the liquidity of an NFT project based on its transaction data to taking a deeper analysis of a newly founded community by its related social data, Adot can fulfill thirsty users with clean, intensive, complete, and well-structured data. ## AI Adot is integrating AI into search engines. AI is a powerful technology to return more accurate, personalized, interactive, and even humanized outputs as mentioned previously. Conversely, sorted, structured, and diverse data available from search engines can also empower AI to train models. --- # Agent Instructions: 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://adot.gitbook.io/adot-whitepaper/protocol-and-product-introduction/highlights/wide-application-scenarios.md?ask= ``` 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.