Amazon Bedrock

Amazon Bedrock

Amazon Bedrock is AWS's managed platform for building generative AI applications and agents in production. Bedrock gives a single API across hundreds of foundation models from the major AI companies, with evaluation tools for picking one on performance and cost, then adds the parts an enterprise deployment needs around it: knowledge bases for grounding on private data, guardrails for safety filtering, fine-tuning for customisation, and AgentCore for running agents built in any framework. It is the AWS counterpart to Google's Vertex AI and Microsoft's Foundry, and the place most AWS-native teams meet generative AI first.

Production credibility: AWS states that more than 100,000 organisations build on Bedrock. The platform publishes measurable safety claims for its Guardrails feature — blocking up to 88% of harmful content and identifying correct responses with up to 99% accuracy to reduce hallucinations — and AgentCore extends it to agent deployment with enterprise security. Billing is consumption-based per token, with provisioned throughput available for steady workloads, and everything runs inside an existing AWS account rather than under a separate vendor contract.

Key Features

• One API across hundreds of foundation models from multiple providers
• Model evaluation tools for choosing on quality and cost
• Knowledge bases for grounding responses in private data
• Guardrails for content filtering and hallucination reduction
• Fine-tuning and continued pre-training on your own data
• AgentCore for deploying agents from any framework with production security

Ideal Use Case

Teams already building on AWS that want model choice without a second vendor relationship, and enterprises whose security review is easier when inference happens inside their existing cloud account. It suits workloads that need grounding on private data and policy enforcement more than they need the newest model on day one.

How Amazon Bedrock differentiates

The three hyperscaler platforms converge on the same shape — model catalogue, grounding, guardrails, agents — so the practical differences are procurement and ecosystem. Bedrock's advantage is that it inherits AWS identity, networking, logging and billing, which removes most of the security-review work for an AWS shop. Against a direct model API such as OpenAI's, you trade a little immediacy for provider choice and enterprise controls; against Vertex AI, the deciding factor is usually which cloud the data already lives in.

FAQ

Q: What is Amazon Bedrock? A: Amazon Bedrock is AWS's managed platform for generative AI. It provides one API across hundreds of foundation models, plus knowledge bases, guardrails, fine-tuning and agent deployment through AgentCore.

Q: How much does Amazon Bedrock cost? A: Bedrock is billed on consumption, priced per token by model, with provisioned throughput available for predictable workloads. Costs appear on your existing AWS bill.

Q: Which models are available on Bedrock? A: Hundreds of foundation models from leading AI companies, accessed through a single API, with built-in evaluation tools for comparing them on quality and cost.

Q: How is Bedrock different from SageMaker? A: SageMaker is AWS's machine learning platform for training and deploying your own models. Bedrock is aimed at building applications and agents on existing foundation models.

Q: Can Bedrock run AI agents? A: Yes. AgentCore deploys agents built in any framework with production-grade security, connecting them to enterprise systems, tools and data.

tl;dr

Amazon Bedrock is AWS's managed generative AI platform: one API over hundreds of foundation models, plus knowledge bases, guardrails, fine-tuning and AgentCore for agents. More than 100,000 organisations use it, billed per token inside an existing AWS account.