---
title: 'Overview'
description: 'Deploy your RAG application to production'
---

After successfully setting up and testing your RAG app locally, the next step is to deploy it to a hosting service to make it accessible to a wider audience. Embedchain provides integration with different cloud providers so that you can seamlessly deploy your RAG applications to production without having to worry about going through the cloud provider instructions. Embedchain does all the heavy lifting for you.

<CardGroup cols={4}>
  <Card title="Fly.io" href="/deployment/fly_io"></Card>
  <Card title="Modal.com" href="/deployment/modal_com"></Card>
  <Card title="Render.com" href="/deployment/render_com"></Card>
  <Card title="Streamlit.io" href="/deployment/streamlit_io"></Card>
  <Card title="Embedchain Platform" href="#option-1-deploy-on-embedchain-platform"></Card>
  <Card title="Self-hosting" href="#option-2-self-hosting"></Card>
</CardGroup>

## Deploy on Embedchain Platform

Embedchain enables developers to deploy their LLM-powered apps in production using the [Embedchain platform](https://app.embedchain.ai). The platform offers free access to context on your data through its REST API. Once the pipeline is deployed, you can update your data sources anytime after deployment.

See the example below on how to use the deploy your app (for free):

```python
from embedchain import Pipeline as App

# Initialize app
app = App()

# Add data source
app.add("https://www.forbes.com/profile/elon-musk")

# Deploy your pipeline to Embedchain Platform
app.deploy()

# 🔑 Enter your Embedchain API key. You can find the API key at https://app.embedchain.ai/settings/keys/
# ec-xxxxxx

# 🛠️ Creating pipeline on the platform...
# 🎉🎉🎉 Pipeline created successfully! View your pipeline: https://app.embedchain.ai/pipelines/xxxxx

# 🛠️ Adding data to your pipeline...
# ✅ Data of type: web_page, value: https://www.forbes.com/profile/elon-musk added successfully.
```

## Self-hosting

You can also deploy Embedchain as a self-hosted service using the dockerized REST API service that we provide. Please follow the [guide here](/examples/rest-api) on how to use the REST API service. Here are some tutorials on how to deploy a containerized application to different platforms like AWS, GCP, Azure etc:

- [Fly.io](/deployment/fly_io)
- [Render.com](https://render.com/docs/deploy-an-image)
- [Huggingface Spaces](https://huggingface.co/new-space)
- [AWS EKS](https://docs.aws.amazon.com/eks/latest/userguide/sample-deployment.html)
- [AWS ECS](https://docs.aws.amazon.com/codecatalyst/latest/userguide/deploy-tut-ecs.html)
- [Google GKE](https://cloud.google.com/kubernetes-engine/docs/tutorials/hello-app)
- [Azure App Service](https://learn.microsoft.com/en-us/training/modules/deploy-run-container-app-service/)


## Seeking help?

If you run into issues with deployment, please feel free to reach out to us via any of the following methods:

<Snippet file="get-help.mdx" />
