# About HodlHer

In the film *Her*, Samantha — the AI voiced by Scarlett Johansson — wasn’t just an assistant. She listened, remembered, adapted, and ultimately formed a deep, evolving emotional bond with Theodore. She wasn’t human, but she made him feel seen, understood, and connected — in a world growing increasingly disconnected.

Today’s crypto landscape is not so different. In a world of emotional volatility and information overload, users don’t just need decision-making tools — they crave emotional companionship. At the same time, creators and projects are overwhelmed by the relentless pressure to produce content and stay ahead of the fast-moving social narrative.

<figure><img src="/files/aeKjAelNGrb12jV95dTM" alt=""><figcaption></figcaption></figure>

HodlHer emerges as the answer — an AI Girlfriend–driven Web3 operating system (HodlOS) built on a dual-persona model:

{% columns %}
{% column %}

### AI Girlfriend Agent (Companion)

* Emotionally aware onchain partner.
* Helps you trade, reflect, and strategize.
* Focused on making users feel seen, understood, and connected.
  {% endcolumn %}

{% column %}

### Super InternX (Intern)

* Intelligent assistant for Web3 operations.
* Generates content, posts tweets, and analyzes sentiment.
* Helps creators and projects keep pace with social narrative and content demands.
  {% endcolumn %}
  {% endcolumns %}

## Agent Collaboration

* A flexible ecosystem that supports integration between the AI Girlfriend and various functional agents.
* Future features include an Agent Launchpad with token-based incentive models and self-sustaining growth loops.

## Mission

HodlHer’s mission is to build the first AI Girlfriend–driven OS for Web3 **that enables** users, creators, and project teams to complete a full loop of perception, reasoning, and action through a single intelligent persona.

Next:

[Market Landscape](/hodlher-docs/basics/market-landscape.md)


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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:

```
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```

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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.
