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Amazon Bedrock

The easiest way to build and scale generative AI applications with foundation models

Amazon Bedrock logo alongside a Softwire visual

Amazon Bedrock

Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies like AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, Stability AI, and Amazon through a single API, along with a broad set of capabilities you need to build generative AI applications with security, privacy, and responsible AI.

Since Amazon Bedrock is serverless, you don’t have to manage any infrastructure, and you can securely integrate and deploy generative AI capabilities into your applications using the AWS services you are already familiar with.

Choose from a range of leading FMs

Amazon Bedrock helps you rapidly adapt and take advantage of the latest generative AI innovations with easy access to a choice of high-performing FMs from leading AI companies like AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, Stability AI, and Amazon.

The single-API access of Amazon Bedrock, regardless of the models you choose, gives you the flexibility to use different FMs and upgrade to the latest model versions with minimal code changes.

Privately adapt models with your data

Deliver more relevant FM responses with RAG

To equip the FM with up-to-date proprietary information, organizations use Retrieval Augmented Generation (RAG), a technique that involves fetching data from company data sources and enriching the prompt with that data to deliver more relevant and accurate responses.

Knowledge Bases for Amazon Bedrock is a fully managed RAG capability that allows you to customize FM responses with contextual and relevant company data. Knowledge Bases for Amazon Bedrock automates the complete RAG workflow, including ingestion, retrieval, prompt augmentation, and citations, removing the need for you to write custom code to integrate data sources and manage queries.

Our work with Bedrock

Softwire worked with a publishing company to trial the usage of Generative AI in repeatable generation of new content based on existing texts, while fitting with the publisher’s style and tone.

Retrieval Augmented Generation (RAG) was utilised to ensure the use of consistent source material backing the generated content. Multiple FMs were exposed via a custom-built web application and Word Processor plugin, including Claude via Amazon Bedrock.

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