HAQM Bedrock in SageMaker Unified Studio

Access HAQM Bedrock's capabilities through SageMaker Unified Studio to quickly build and customize your generative AI applications. This intuitive interface lets you work with high-performing foundation models (FMs) and use advanced features like HAQM Bedrock Knowledge Bases, HAQM Bedrock Guardrails, HAQM Bedrock Agents, and HAQM Bedrock Flows. You can develop generative AI applications faster within SageMaker Unified Studio's secure environment, ensuring alignment with your requirements and responsible AI guidelines.

With HAQM Bedrock in SageMaker Unified Studio, you can develop generative AI applications through a simple, accessible experience designed for developers of all skill levels. The intuitive interface enables teams to collaborate effectively while using HAQM Bedrock's capabilities. You can access governed data, quickly prototype, iterate, and deploy production-ready generative AI apps based on your business needs.

Customize FMs to match your requirements, data, workflows, and responsible AI standards. Create Knowledge Bases from your proprietary data sources using Retrieval Augmented Generation (RAG) to tailor your model responses to business needs. Build chat agent apps using Agents, add Guardrails for safeguarding and privacy, and leverage advanced features like prompt engineering, functions, and Flows – all without managing underlying services.

Using HAQM Bedrock in SageMaker Unified Studio, you can collaborate seamlessly across business and technical teams, regardless of skill level. You can build, customize, and share generative AI applications securely, enabling trusted teamwork across functions. This helps your teams create various solutions, from company-specific content generation to workflow automation and software development.

Access a wide range of high-performing FMs from leading AI companies through the generative AI playground. You can compare different models and configurations to evaluate their performance easily. Using automated model evaluation, you can identify and select the best model for your use case based on performance, quality, and safety metrics.

Create guardrails and set content filters on both user input and model responses to ensure appropriate outputs from your generative AI app. Customize guardrail behavior by adjusting filtering levels across categories and adding denied topics, aligning with your responsible AI guidelines and desired outputs.

We build complex data analytics, ML and GenAI applications with built-in data governance and user-friendly interfaces. Before HAQM SageMaker Unified Studio, deploying multiple tools for our customers' data and information workers was mostly manual and time-consuming, and ensuring a robust data architecture provisioning was a challenge. Now, with HAQM SageMaker Unified Studio, we can deploy a single data worker tool for data engineers and ML scientists. We are also automating data infrastructure deployment, allowing us to simplify the process for our customers and enhance their experience.

To address siloed data sets spread across our automotive operations, we are implementing HAQM SageMaker to help unify and govern data across our connected car, sales, manufacturing, and supply chain units. This approach allows us to search, discover, and share data effortlessly, laying the groundwork to pre-empt quality issues, increase customer satisfaction, and enable easier development of generative AI applications.