# What You Can Do with Kinesis

**Run AI and LLM workloads**\
Deploy, fine-tune, and serve machine learning models using high-performance GPU infrastructure, with the flexibility to scale as demand changes.

**Build and operate data pipelines**\
Execute batch and streaming workloads efficiently, with the ability to adapt compute resources to changing data volumes.

**Optimize cost and utilization**\
Choose between on-demand, usage-based compute or pre-configured resources, and gain a unified view of performance and spend across your workloads.

**Leverage existing infrastructure**\
Connect your own compute resources to Kinesis and manage them alongside platform-provided capacity, all within a single control plane.

**Standardize your runtime environment**\
Use container-based deployments to ensure consistency across development, testing, and production environments.


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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://docs.kinesis.network/what-you-can-do-with-kinesis.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.