- Amazon Bedrock in one clear definition
- Which AI models you can reach through Bedrock
- What you can build with Amazon Bedrock
- Amazon Bedrock and your business data
- How to start with Amazon Bedrock
- Who Amazon Bedrock is for, and who it isn't
- Questions to ask a supplier who builds on Amazon Bedrock
- Amazon Bedrock compared with other AI platforms
- Frequently asked questions
AWS Bedrock (Amazon Bedrock) is a managed service on Amazon's cloud that lets developers use many AI foundation models through one connection to build generative AI apps. It's a toolkit, not a chat app. The part people trip over: AWS says Bedrock never stores or uses your data to train models, but you still manage your own settings.
If a developer, agency or IT supplier has mentioned Amazon Bedrock to you, it can sound like yet another bit of cloud jargon. It matters because a growing number of AI features inside business software are built on services like it. You don't need to use it yourself, but knowing what it is helps you ask the right questions.
Amazon Bedrock in one clear definition
AWS's documentation describes Amazon Bedrock as a fully managed service that provides secure, enterprise-grade access to high-performing foundation models from leading AI companies, so you can build and scale generative AI applications.
In plain words: a foundation model is a large, ready-made AI model, the kind behind chat assistants and image generators. Bedrock is a single place on Amazon's cloud where a business can reach many of those models through one connection, instead of signing separate agreements and building separate plumbing for each. It is a builder's toolkit rather than a chat app you open and type into.
Which AI models you can reach through Bedrock
The AWS docs say Bedrock supports 100+ foundation models from providers including Amazon, Anthropic, DeepSeek, Moonshot AI, MiniMax, OpenAI and xAI. Which models are on offer, and in which regions, changes often, so check the model list in the AWS documentation rather than trusting any article, mine included.
The practical benefit is choice. A team can try one model for drafting text, another for summaries and a third for something else, without rebuilding the app each time. AWS also lists tools to compare models against each other.
What you can build with Amazon Bedrock
AWS lists several building blocks on its Bedrock page. Here are the ones a business owner is most likely to hear about:
- Knowledge Bases. These connect a model to your own documents so its answers draw on your material. AWS describes the method as retrieval augmented generation (RAG): a knowledge base searches your data for relevant information, and the answer can include citations back to the source.
- Guardrails. Safety settings that filter what goes into and comes out of a model.
- Agents. AI helpers that can carry out multi-step tasks, which AWS builds through its AgentCore platform.
- Customisation. Options such as fine-tuning to adapt a model to a specific job.
If agents are new to you, my guide to what AI agents are and how a business can use them is a gentle start, and the AI agent guardrails checklist shows the sort of limits worth setting.
Amazon Bedrock and your business data
This is the question I'd put first, and AWS answers it directly. Its Bedrock page says Bedrock never stores or uses your data to train models. The data-protection documentation adds that model providers have no access to the Bedrock deployment accounts, so they don't see Bedrock logs or customer prompts and completions.
That doesn't mean you can stop thinking. AWS runs on a shared responsibility model, where AWS secures the infrastructure and you're responsible for your own content and settings. The docs advise using multi-factor authentication, giving each person only the permissions they need, and never putting confidential details such as customers' email addresses into free-form fields like a Name field.
How to start with Amazon Bedrock
The service is built for people comfortable with cloud accounts, so the honest route for most business owners is to have a developer or consultant do the set-up. If you want to look yourself, AWS documents the general path:
- Create or sign in to an AWS account and open the Amazon Bedrock section of the console.
- Check which models are available in your region.
- Try a model in the console, or follow the Quickstart in the docs, which says you can write your first API call in under five minutes.
- Add Knowledge Bases or Guardrails once you know what the application needs to do.
Menus and model access rules change, so follow the current AWS user guide rather than any screenshot.
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Who Amazon Bedrock is for, and who it isn't
Bedrock suits teams building their own AI features, such as a support assistant that answers from product manuals, or an internal search over company documents. Typical users are developers, agencies and in-house technical staff.
It's probably not the right starting point if you simply want to draft emails or summarise a meeting. A ready-made assistant is quicker for that. For a sense of what's available off the shelf, see my roundup of the best AI tools for small business owners.
Questions to ask a supplier who builds on Amazon Bedrock
If an agency says your project will run on Bedrock, a few plain questions keep everyone honest:
- Which model are you using, and what happens to the project if that model changes?
- Will it answer from my own documents, and how will those be kept up to date?
- What guardrails will stop it saying things I wouldn't say to a customer?
- Which AWS account will it run in, mine or yours, and who can see the data?
- How will we check the answers before customers see them?
Amazon Bedrock compared with other AI platforms
Google Cloud has a similar service in Vertex AI, now part of Gemini Enterprise Agent Platform. The broad idea is the same: a managed place to use models inside the cloud you already run on. Many businesses choose the one that matches the cloud they already use for everything else.
Frequently asked questions
What is AWS Bedrock?
Amazon Bedrock is a managed service on Amazon's cloud that gives developers access to many foundation models from different AI companies through one service, for building generative AI applications.
Is Amazon Bedrock a chatbot I can use?
Not in the way ChatGPT is. It's a toolkit for building AI features into apps and workflows, normally set up by a developer.
Does Amazon Bedrock use my data to train models?
AWS says Bedrock never stores or uses your data to train models. Read the current data protection pages in the AWS documentation for the exact terms before you rely on this.
Which AI models are available on Bedrock?
AWS says it supports 100+ models from providers including Amazon, Anthropic, OpenAI, DeepSeek and xAI. The list varies by region and changes often, so check the docs.
What are Bedrock Knowledge Bases?
They connect a model to your own documents using retrieval augmented generation, so answers can draw on your material and include citations.
Do I need to be a developer to use Amazon Bedrock?
In practice, mostly yes. The console is approachable for experiments, but building something dependable usually needs technical help.
