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Amazon Bedrock
The easiest way to build and scale generative AI applications with foundation models
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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.
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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
Model customization helps you deliver differentiated and personalized user experiences. To customize models for specific tasks, you can privately fine-tune FMs using your own labeled datasets in just a few quick steps.
Amazon Bedrock supports fine-tuning for Cohere Command, Meta Llama 2, Amazon Titan Text Lite and Express, Amazon Titan Multimodal Embeddings, and Amazon Titan Image Generator. To adapt Amazon Titan Text models to your industry and domain, you can use continued pretraining with unlabeled data.
With fine-tuning and continued pretraining, Amazon Bedrock makes a separate copy of the base FM that is accessible only by you, and your data is not used to train the original base models.
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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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Our insights
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Talk 1-1 with a consultant
Book a call with one of our consultants to discuss your challenges.