> ## Documentation Index
> Fetch the complete documentation index at: https://docs.neum.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Deploy pipelines

> Deploy your pipelines to Neum AI Cloud

Neum AI provides a managed cloud enviornment to run and manage your pipelines. It offers capabilities like pipeline management, run scheduling, automatic synchronization as well as a high scale distributed architecture to run large jobs. Learn more about the difference between [Local and Cloud enviornments for Neum AI](/get-started/cloud-vs-local).

<Note>Prerequisite: Make sure you have already configured you Neum AI pipeline in our [quickstart](/get-started/quickstart).</Note>

<Note>You will need a Neum AI API Key. Get one by going to [dashboard.neum.ai](https://dashboard.neum.ai) and creating an account. It's free!</Note>

## Test pipeline locally

Before we deploy the pipeline to Neum AI Cloud, lets run a quick local test to make sure things are working as expected.

<Steps>
  <Step title="Validate">
    Run a local validation of the pipeline

    ```Python Local validation
    print("Pipeline validation successful? " + pipeline.validate())
    ```
  </Step>

  <Step title="Test pipeline">
    Run a test to make sure the pipeline runs smoothly end to end

    ```Python Local run
    result = pipeline.run()
    info = pipeline.sink.info()
    print("Vectors written in pipeline run: " + result) 
    print(info)
    ```
  </Step>

  <Step title="Test search">
    Finally, lets test the stored vectors

    ```Python Local search
    results = pipeline.search(query="What are the challenges with scaling RAG?", number_of_results=3)

    for result in results:
      print(result.metadata)
    ```
  </Step>
</Steps>

## Deploy pipeline to Neum AI Cloud

To deploy the pipeline, we will leverage the built-in functions.

<Note>You will need a Neum AI API Key. Get one by going to [dashboard.neum.ai](https://dashboard.neum.ai) and creating an account.</Note>

```python Deploy to cloud
from neumai.Client.NeumClient import NeumClient

neumClient = NeumClient(api_key = '<INSERT NEUMAI API KEY>')
neumClient.create_pipeline(pipeline=pipeline)
```

Once deployed, you can go to [Neum AI Cloud dashboard](dashboard.neum.ai) to see the status and pipeline information. Alternatively, you can programmatically query:

### Get pipeline information

```python Deploy to cloud
from neumai.Client.NeumClient import NeumClient

neumClient = NeumClient(api_key = '<INSERT NEUMAI API KEY>')
neumClient.get_pipeline(pipeline_id='<pipeline_id from above>')
```

### Search pipeline

```python Deploy to cloud
from neumai.Client.NeumClient import NeumClient

neumClient = NeumClient(api_key = '<INSERT NEUMAI API KEY>')
neumClient.search_pipeline(pipeline_id='<pipeline_id from above>', query=<search query>)
```