---
title: Introduction
description: RamaLama strives to make working with AI simple, straightforward, and familiar by using OCI containers.
sidebar_position: 0
---

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<img src="https://github.com/user-attachments/assets/1a338ecf-dc84-4495-8c70-16882955da47" style={{width: "50%"}} />
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[RamaLama](https://ramalama.ai) strives to make working with AI simple, straightforward, and familiar by using OCI containers.

## Description
RamaLama is an open-source tool that simplifies the local use and serving of AI models for inference from any source through the familiar approach of containers. It allows engineers to use container-centric development patterns and benefits to extend to AI use cases.

RamaLama eliminates the need to configure the host system by instead pulling a container image specific to the GPUs discovered on the host system, and allowing you to work with various models and platforms.

- Eliminates the complexity for users to configure the host system for AI.
- Detects and pulls an accelerated container image specific to the GPUs on the host system, handling dependencies and hardware optimization.
- RamaLama supports multiple AI model registries, including OCI Container Registries.
- Models are treated similarly to how Podman and Docker treat container images.
- Use common container commands to work with AI models.
- Run AI models securely in rootless containers, isolating the model from the underlying host.
- Keep data secure by defaulting to no network access and removing all temporary data on application exits.
- Interact with models via REST API or as a chatbot.


## Contributors

Open to contributors

<a href="https://github.com/containers/ramalama/graphs/contributors">
  <img src="https://contrib.rocks/image?repo=containers/ramalama" />
</a>