Generative AI for Enterprise Environments

, allowing AWS customers to access Cohere’s models as an API, eliminating the need to manage the underlying infrastructure.

Customers can easily access Cohere’s models and incorporate AI features into their applications and workflows without the need to train models or build the infrastructure required for deploying and managing LLMs.

With Cohere on AWS, customer data remains securely managed and protected. AWS provides enterprise-grade security and privacy tools integrated into the environment, enabling encryption, access control, and privacy.

Amazon Bedrock and Amazon SageMaker are optimized for AI workloads, with high-performance compute, storage, and networking resources. It’s fully managed, which makes it easy to deploy Cohere’s models at scale.

Cohere’s models are trained from scratch from known, purchased, or public domain data sources and are subject to extensive adversarial testing and bias mitigation.

Generative AI capabilities for secure enterprise environments

Build financial search applications using multilingual embedding model

AWS Machine Learning Blog

Bedrock now provides access to Cohere Command Light and Embed models

AWS News blog

Announcing New Tools to Help Every Business Embrace Generative AI

AWS Machine learning blog

GitHub

SaaS

supporting

time to get started

benefits

limitations

pricing structure

Best for


Get started with LLMs instantly through Cohere's Software as a Service (SaaS) platform, all without managing backend infrastructure.


Private Deployments

Compute and infrastructure management required

Organizations with strict data residency requirements

Need for maximum control and customization

Organizations dealing with sensitive or customer data

Bring Cohere's models into your own infrastructure, whether in the cloud or on-premises. Maintain a high level of security and control over sensitive information.

For ultimate customization and control over security

Cloud AI Platforms

Deployment depends on cloud provider features

Companies seeking easy integration with cloud service

Use Cohere's models through a variety of platforms such as Amazon SageMaker, Amazon Bedrock, OCI Generative AI, etc.



For running Cohere’s models across cloud AI platforms

Access Cohere’s generative and representative models in private Amazon Bedrock and Amazon SageMaker environments.

Developers can access a range of Cohere language models in a private environment via Amazon’s AWS Cloud platform. Cohere’s models are supported on two Amazon services: **Amazon SageMaker** and **Amazon Bedrock**.

### Amazon SageMaker

Amazon SageMaker is a service that allows customers to prepare data and build, train, and deploy machine learning (ML) models for any use case with fully managed infrastructure, tools, and workflows. [Read about SageMaker here.](https://aws.amazon.com/pm/sagemaker/)

Cohere offers a comprehensive suite of generative and embedding models through SageMaker on a range of hardware options, many of which support finetuning for deeper customization and performance.

 [View Cohere's products on Amazon SageMaker](https://aws.amazon.com/marketplace/seller-profile?id=87af0c85-6cf9-4ed8-bee0-b40ce65167e0).

### Amazon Bedrock

**Amazon Bedrock** is a fully managed service where foundational models from Cohere and other LLM providers are made available through a single, serverless API. [Read about Bedrock here](http://docs.aws.amazon.com/bedrock).

Cohere has two flagship offerings available on-demand through Bedrock: Command and the Embed v3 family of models. Finetuning is also supported for the Command and Command-Light models. Cohere will continue to add products and services to Bedrock in the coming months. 

[View Cohere’s products on Amazon Bedrock](https://us-east-1.console.aws.amazon.com/bedrock/home?region=us-east-1#/providers?model=command)

### Python SDK

The Cohere Python SDK supports both Amazon SageMaker and Amazon Bedrock. The SDK provides a simple and consistent interface for interacting with Cohere models across platforms.

[cohere-aws SDK on Github](https://github.com/cohere-ai/cohere-aws)

### Pricing

The latest pricing for Cohere models can all be viewed directly from from the listing pages on our Amazon Bedrock and Amazon SageMaker marketplaces. If you have any questions about pricing or deployment options, [please contact our sales team.](https://cohere.com/contact-sales)

Cohere on AWS

We charge differently for input and output tokens. You are charged based on the sum of tokens processed. Fine-tuning inference costs will be the same as our base models.

Each text (input) classified counts as one classification. You are not charged for examples provided.

Embeddings perform best when the text to be embedded is less than 512 tokens. You can create up to 96 embeddings per API call.

We charge differently for input and output tokens. You are charged based on the sum of tokens processed. Only Command Light is available for fine-tuning at this moment. Fine-tuning inference costs will be the same as our base models.

We count a single search unit as a query with up to 100 documents to be ranked. Documents longer than 510 tokens when including the length of the search query will be split up into multiple chunks, where each chunk counts as a singular document. Fine-tuning inference costs will be the same as our base models.

We charge differently for input and output tokens. You are charged based on the sum of tokens processed.

Generative AI for Enterprise Environments

Cohere Models on AWS

AWS resources