AWS Generative AI Bedrock

At some point in their existence, most organizations will inevitably reach a point where they are ready to grow or scale their business, but aren’t quite sure, logistically, how they can make it happen. They want to be efficient in their approach, without leaving much room for error or confusion.

In many ways, organizational growth presents a gauntlet for business leaders—a series of high-impact decisions they must make that will set the stage for their future without compromising their strengths. For forward-thinking organizations that are looking to scale their business and keep up with the times, generative AI—GenAI for short—has been an absolute game-changer.

One of the biggest challenges for a growing business is making a wide range of timely, data-backed decisions—rather than relying purely on instinct or simply doing things the way they’ve already been done. Making such decisions requires not only a vast collection of data, but the ability to verify its accuracy, synthesize and summarize it, and uncover actionable insights for improvement.

That’s where GenAI can be so powerful—its ability to evaluate and analyze ever-growing and ever-more-complex datasets, at scale, is simply not something that is feasible without these impressive tools, such as those provided by Amazon Web Services (AWS) such as Amazon Bedrock.

So, what exactly is Amazon Bedrock? What can it be used for? Is it worth it? You’ll find these answers and more in this informative article.

Does AWS Have Generative AI Tools for Businesses?

Yes, AWS offers a range of solutions powered by GenAI, including a suite of ready-to-use business applications as well as tools for building your own GenAI applications. In this article, we’re going to focus specifically on an application in the latter class—Amazon Bedrock.

What Is AWS Bedrock?

Amazon Bedrock is described as a “fully managed service that makes high-performing foundation models (FMs) from leading AI startups and Amazon available for your use through a unified API.” In other words, it’s a service that empowers organizations to not only leverage existing AI models, but to design and launch new models and capabilities as well.

It might help to think about it like this: conventional AI and machine learning services are great at what they do—synthesizing and summarizing massive amounts of data–but what they do is limited. Generative AI, by contrast, takes those capabilities a significant step further by actually creating new data and content. To learn more, we recommend checking out the online AWS Bedrock User Guide here.

What Is the Difference Between SageMaker JumpStart and Bedrock?

Amazon Bedrock and SageMaker JumpStart are considered the two centerpieces of AWS’s artificial intelligence and machine learning services. In many ways, the pair serves as the cornerstone components of AWS Generative AI’s offerings. As DEV Community notes,

  • Amazon Bedrock “is a fully managed service that provides access to pre-trained foundation models from Amazon/AWS and well-known AI startups,”
  • Amazon SageMaker “is a comprehensive service that allows data scientists and developers to build, train, and deploy machine learning models for extended use cases.”

Rather than thinking about these two products’ differences, they are not a “one or the other” proposition. Instead, they work together—potentially with other services, too, to deliver the most value. As Amazon notes, both “provide native integration to use a variety of generative AI tools with your Security Lake data to help increase your organization’s security posture.”

Does AWS Have a ChatGPT Equivalent?

While Amazon Bedrock isn’t necessarily a ChatGPT equivalent—it’s capable of so much more than chatbots—AWS does offer similar chatbot functionality in the form of Amazon Q. Even this comparison is incomplete, though, since in addition to ChatGPT-style chatbots, Amazon Q also includes features that can help with generating code, answering questions, and more.

What Is Amazon Bedrock Used For?

Like many emerging GenAI solutions, the number of potential use cases for Amazon Bedrock is ever-growing, making it a particularly powerful tool for organizations that might want to


  • Create a better customer experience. Many customers prefer quick self-service options when they have a quick issue or question. By leveraging Amazon Bedrock, you can create chatbots and virtual assistants to handle a wide range of interaction types. You can also enhance agents’ ability to help customers quickly and effectively with agent assist features like task automation and enhanced knowledge base searches.
  • Enhance the agent experience and productivity. Amazon Bedrock can transform the agent experience by automating repetitive tasks and making it easier for them to quickly find the resources and answers they need (in turn, improving the customer experience as well). Amazon Bedrock can also accelerate app development through code generation, automated report generation, and other functions.
  • Take content creation to the next level. Whether it relates to sales or marketing, creating and promoting engaging content is one of the most important things an organization can do to attract and retain customers. Like code generation, creating written content requires both efficiency and creativity—that doesn’t mean it’s out of the realm of what GenAI can accomplish, however. It can even help with product development, prototyping, and more.
  • Optimize internal processes. There are countless ways an organization can use existing AI tools to streamline their internal processes and workflows. The development of GenAI applications in particular, then, takes these capabilities even further and allows for further evolution in how they’re able to process documents and extract insights. And in situations where there isn’t a lot of existing data to train models on, Amazon Bedrock can generate synthetic data.

Can Amazon Bedrock Generate Code As Well as Developers Can?

Yes, Amazon Bedrock is highly capable when it comes to code generation as well as bug detection and other related actions. This enables organizations to automate many functions, which in turn frees up their employees for other tasks.

Even with AI being increasingly understood by the “mainstream,” many companies are still a little wary about using these tools—which is unfortunate when you consider how much more productive they could be! That being said, you might be thinking, “we have a team of proficient developers, why do we need to bring AI into the equation?”

And while you’re not wrong (humans are, in fact, just as capable of generating code), GenAI tools like AWS bedrock can automate “low-value” tasks (like basic code generation), so your team of developers can focus on other projects without getting bogged down in the onslaught of data that’s being created virtually every minute.

How Does Amazon Bedrock Improve Code Quality and Security?

When used properly, a GenAI solution like Amazon Bedrock can not only create code efficiently and competently, it also improves code quality and security through capabilities like automated code analysis. By offering “a choice of high-performing foundation models (FMs) from leading AI companies,” Amazon Bedrock provides an unprecedented versatility.

  • For the uninitiated, foundation models are a specific form of AI that “generate[s] output from one or more inputs (prompts) in the form of human language instructions.” They can be pre-trained on existing datasets, but they can also continue to learn as they go, as long as they are provided with specific, well-crafted prompts. Foundation models can achieve quite a lot for an organization. In addition to code generation, they’re also adept with things like language processing, visual comprehension, and even human-centered engagement (in other words, helping users to make informed and timely decisions based on the available data).

Amazon Bedrock is a flexible and comprehensive solution that enables developers to experiment with and build their own secure—and responsible—GenAI applications, providing everything you need to create your own powerful applications, along with the ability to


  • Work with your preferred model choice. The AWS Bedrock API key offers single API access through a , meaning you won’t be limited to a narrow set of options and it won’t be difficult to evaluate and experiment with them, so you can develop the best application(s) for your intended use case. Learn more about the developer experience here.
  • Adapt your data models to create more customized experiences. Customers across countless industries increasingly expect a personalized experience, and AWS Bedrock makes it easy to customize and fine-tune your FMs as needed. This enables your organization to be even more agile—and to leverage even greater insights to guide their decision-making and overall strategy.

When Was AWS Bedrock Released?

Amazon Bedrock was originally announced in April of 2023, with its general availability then announced in September 2023. What it brought to the marketplace was something new: a way for organizations to leverage industry-leading foundation models within a single API access.

Is Llama2 Available in Bedrock?

Yes, Llama 2 is one of the available Amazon Bedrock models—so are Amazon Titan, Claude, Command & Embed, Jurassic, and others.

What Can Amazon Bedrock’s GenAI Solution Do for Your Business—and How Can We Help?

Over the course of this article, we’ve introduced a wide variety of features and use cases for Amazon Bedrock. If you’re still unsure whether it’s right for your organization—or the best way to get started—don’t hesitate to reach out to InterVision Systems. We’re a managed services provider whose mission is to empower companies with the insights and support they need to take their business to the next level through the adoption of GenAI and other modern innovations.

To learn more, consider signing up for one of our workshops dedicated to GenAI strategy and use case workshops. We can also facilitate a GenAI readiness assessment to help you understand where your business stands and identify its best opportunities to innovate or optimize key processes.