> For the complete documentation index, see [llms.txt](https://docs.2pm.network/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.2pm.network/ecosystem/use-cases/private-personalized-recommendation.md).

# Private Personalized Recommendation

2PM.Network envision a future where ecosystems are constructed around high-traffic platforms like Telegram, serving as gateways to vertically integrated application interfaces. Users will have the capability to locally save their interaction history with each application, which, combined with application tags, will be encrypted using fully homomorphic encryption before being uploaded to the DA-layer blockchain. This innovative approach ensures that user data remains private and secure, while still being utilizable for network operations.

To enhance user engagement and utility, 2PM.Network is set to develop a specialized privacy-focused recommendation model. This model will intelligently suggest applications based on individual user behaviors and preferences, fostering a more personalized and engaging user experience. The potential of such a recommendation model extends beyond just app suggestions, encompassing token recommendations, influencer endorsements, and other domains, opening up new avenues for personalized content and service delivery in the decentralized web. This strategy not only enhances user satisfaction but also drives network growth by promoting relevant and tailored interactions within the ecosystem.

<figure><img src="/files/No954QXm7PvqlYSSdu4q" alt=""><figcaption></figcaption></figure>


---

# 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://docs.2pm.network/ecosystem/use-cases/private-personalized-recommendation.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.