# Use Case

## AI-powered Web3 Universal Search Engine

Adot aspires to cover a broad scale of of Web3-related data, including but not limited to on-chain asset data(e.g. NFTs, Tokens), user decentralized identifiers, and linked data (e.g. user wallet addresses, user social media accounts), project and content data scattered in Web2 pages and decentralized storage. Empowered by AI technologies such as NLP and knowledge graph, Adot leverages the structured data available in Web3 and catches either strong or weak connections across entities to build a smart and universal search engine with unlimited potential.

## Open-source Data Services and Tools for Developers

Adot believes in the power and spirit of open source. If you are building any dApp, Adot can provide customized API interfaces and unified data query tools, which not only allow you to query data according to your personalized needs but also easily implement data indexing and parsing functions to sharply reduce development and deployment costs.

## Customized Search Services for Various Needs

Through aggregating massive Web3-related content, Adot itself is an unbeatable database. Further powered with the composability feature of Web3, Adot is supposed to support developers across different fields to build respective search engine applications equipped with indexed data that has a high coverage but without redundant, loaded but unrelated information.


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# 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/use-case.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.
