# Slai

## Docs

- [Model](https://docs.slai.io/api-reference/model.md): The model class is the entry point for your deployed model.
- [API Keys](https://docs.slai.io/dashboard/keys.md): Configure API Keys
- [Tracking Usage](https://docs.slai.io/dashboard/tracking-usage.md): Slai charges usage based billing for the compute used to train and deploy your apps.
- [Connecting to Google BigQuery](https://docs.slai.io/integrations/connecting-bigquery.md): Slai supports direct integration with Google BigQuery. This guide demonstrates how to retrieve data from BigQuery for use in a Slai Sandbox.
- [Connecting S3 Buckets](https://docs.slai.io/integrations/connecting-s3-buckets.md): Slai comes with several integrations to import data from remote data stores, like S3 buckets. This guide explain how to connect an S3 bucket and use it in your sandbox.
- [Import Code from Github](https://docs.slai.io/integrations/import-code-from-github.md)
- [Shipping Metrics Outside Slai](https://docs.slai.io/integrations/shipping-metrics-outside-slai.md): Shipping metrics to a third party tool is fairly straightforward. In this example, we'll log our training metrics to Weights and Biases (WandB) to track our experiments.
- [Slack Notifications](https://docs.slai.io/integrations/slack-notifications.md)
- [What is Slai?](https://docs.slai.io/introduction.md): Slai is the fastest way for developers to build machine learning applications that can be deployed on serverless infrastructure and shared with anyone in the world.
- [Usage-Based Billing](https://docs.slai.io/pricing/usage-based-billing.md)
- [Debugging Guide](https://docs.slai.io/resources/debugging-guide.md)
- [Datasets](https://docs.slai.io/sandbox/datasets.md): Add data to your sandbox.
- [Dependencies](https://docs.slai.io/sandbox/dependencies.md): How to add dependencies to your environment
- [Deployments](https://docs.slai.io/sandbox/deployments.md): Your model can be deployed as a real-time API. Slai includes client libraries for cURL, Python, and Node, allowing you to call the deployed model from your own codebase.
- [Handler](https://docs.slai.io/sandbox/model-handler.md): Building logic around a hosted model.
- [Revisions](https://docs.slai.io/sandbox/model-versions.md): An introduction to model revisions on Slai.
- [Testing](https://docs.slai.io/sandbox/testing.md): Interactively testing a model in the sandbox.
- [Train](https://docs.slai.io/sandbox/train.md): Training a model in Slai.
- [Privacy Policy](https://docs.slai.io/security/privacy-policy.md)
- [Platform Terms and Conditions](https://docs.slai.io/security/terms-and-conditions/platform-terms-and-conditions.md)
- [Website Terms of Service](https://docs.slai.io/security/terms-and-conditions/website-terms-of-service.md)
- [Advanced Deployment Options](https://docs.slai.io/user-guides/advanced-deployment-options.md)
- [Custom Docker Images](https://docs.slai.io/user-guides/custom-docker-images.md)
- [Migrating an existing model](https://docs.slai.io/user-guides/migrating-an-existing-model.md): Already have a model you'd like to migrate to Slai? Here's how to port it over.
- [Using Pre-Trained Models](https://docs.slai.io/user-guides/pre-trained-models.md): Here's a quick guide on how to use pre-trained models in Slai.
- [Recommendation System](https://docs.slai.io/user-guides/recommendation-system.md)

## Optional

- [Launchpad](https://www.slai.io/launchpad)
- [Chat with us](https://calendly.com/elimernit/slai-discovery-call)
- [Migrate Your Model](https://docs.slai.io/user-guides/migrating-an-existing-model)