# Use cases

## Applications of IPC

Here are some practical examples of how IPC improves the performance of dApps:

* **Distributed Computation**: Spawn ephemeral subnets to run distributed computation jobs.
* **Coordination**: Assemble into smaller subnets for decentralized orchestration with high throughput and low fees.
* **Localization**: Leverage proximity to improve performance and operate with very low latency in geographically constrained settings.
* **Partition tolerance**: Deploy blockchain substrates in mobile settings or other environments with limited connectivity.

With better performance, lower fees and faster transactions, IPC can rapidly improve horizontal and vertical markets with decentralized technology:

* **Artificial Intelligence:** IPC is fully compatible with [Filecoin](https://docs.filecoin.io/basics/what-is-filecoin), the world’s largest decentralized data storage. Leveraging Filecoin, IPC can enable distributed computation to power hundreds of innovative AI models.
* **Decentralized Finance (DeFi):** Enabling truly high-frequency trading and traditional backends with verifiability and privacy.
* **Big Data and Data Science:** Multiple teams are creating global-scale distributed compute networks to enable Data Science analysis on Exabytes of decentralized stored data.
* **Metaverse/Gaming:** Enabling real-time tracking of player interactions in virtual worlds.
* **DAOs:** Assemble into smaller subnets for decentralized orchestration with high throughput and low fees. Partition tolerance: Deploy blockchain substrates in mobile settings or other environments with limited connectivity.


---

# 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://docs.ipc.space/overview/use-cases.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.
