# Voyage AI Documentation > Voyage AI provides cutting-edge embedding models for retrieval-augmented generation (RAG). ## Guides: GET STARTED - [Introduction](https://docs.voyageai.com/docs/introduction.md) - [API Key and Python Client](https://docs.voyageai.com/docs/api-key-and-installation.md) - [Quickstart Tutorial](https://docs.voyageai.com/docs/quickstart-tutorial.md) ## Guides: CAPABILITIES - [Text Embeddings](https://docs.voyageai.com/docs/embeddings.md) - [Contextualized Chunk Embeddings](https://docs.voyageai.com/docs/contextualized-chunk-embeddings.md) - [Multimodal Embeddings](https://docs.voyageai.com/docs/multimodal-embeddings.md) - [Rerankers](https://docs.voyageai.com/docs/reranker.md) ## Guides: GUIDES - [Tokenization](https://docs.voyageai.com/docs/tokenization.md) - [Flexible Dimensions and Quantization](https://docs.voyageai.com/docs/flexible-dimensions-and-quantization.md) - [Batch Inference](https://docs.voyageai.com/docs/batch-inference.md) - [Error Codes](https://docs.voyageai.com/docs/error-codes.md) - [Rate Limits](https://docs.voyageai.com/docs/rate-limits.md) - [Pricing](https://docs.voyageai.com/docs/pricing.md) - [Organizations and Projects](https://docs.voyageai.com/docs/organizations-and-projects.md) - [Service Level Objectives](https://docs.voyageai.com/docs/service-level-objectives.md) ## Guides: DEPLOYMENT ON VPC - AWS Marketplace Model Package - [MongoDB Voyage AI Models in AWS](https://docs.voyageai.com/docs/aws-marketplace-mongodb-voyage.md): Deploy MongoDB Voyage AI models using AWS Marketplace - [Voyage AI Models in AWS](https://docs.voyageai.com/docs/aws-marketplace-voyage.md): Deploy Voyage AI models using AWS Marketplace - Azure Marketplace Managed Application - [MongoDB Voyage AI Models in Azure](https://docs.voyageai.com/docs/azure-marketplace-mongodb-voyage.md): Deploy MongoDB Voyage AI models using Azure Marketplace - [Voyage AI Models in Azure](https://docs.voyageai.com/docs/azure-marketplace-voyage.md): Deploy Voyage AI models using Azure Marketplace ## Guides: Community - [Integrations](https://docs.voyageai.com/docs/integrations-and-other-libraries.md) - [Community SDKs](https://docs.voyageai.com/docs/community-sdks.md) ## Guides: HELP - [FAQ](https://docs.voyageai.com/docs/faq.md) - [Contact Email](https://docs.voyageai.com/docs/contact-email.md) - [Discord](https://docs.voyageai.com/docs/discord.md) ## API Reference: Voyage API - Inference - [Text embedding models](https://docs.voyageai.com/reference/embeddings-api.md): The Voyage text embedding endpoint receives as input a string (or a list of strings) and other arguments such as the preferred model name, and returns a response containing a list of embeddings. - [Contextualized chunk embedding models](https://docs.voyageai.com/reference/contextualized-embeddings-api.md): The Voyage contextualized chunk embedding endpoint accepts document chunks—in addition to queries and full documents—and returns a response containing contextualized chunk vector embeddings. These… - [Multimodal embedding models](https://docs.voyageai.com/reference/multimodal-embeddings-api.md): The Voyage multimodal embedding endpoint returns vector representations for a given list of multimodal inputs consisting of text, images, or an interleaving of both modalities.