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Cloud Native Generative AI

Advancing Generative AI with AWS Bedrock

In the first part of the post, I discussed about taking part in a hackathon by building a Mediverse Bot, a Generative AI Medical Application, emphasizing the AWS innovation in Generative AI offerings, comprehensive vector database offerings, and design & architecture of Mediverse Bot

Recognizing the transformative potential of generative AI, AWS has introduced a groundbreaking service called AWS Bedrock. This service is designed to empower organizations to build and scale generative AI applications seamlessly, leveraging state-of-the-art foundation models (FMs). In this blog, we’ll delve deep into AWS Bedrock, exploring its features, capabilities, and how it’s reshaping the generative AI landscape. Of course, briefly discuss the changes made to the Mediverse Bot and its integration with AWS Bedrock.

Deep Dive into AWS Bedrock

Launched in April 2023, AWS Bedrock is a fully managed service that simplifies the development of generative AI applications while ensuring privacy and security. It provides access to high-performing foundation models from leading AI companies, including AI21 Labs, Anthropic, Cohere, Stability AI, and Amazon. With AWS Bedrock, users can experiment with various FMs, customize them with their data, and create managed agents for complex business tasks, all without writing a single line of code.

Why should I Use Bedrock?

Amazon Bedrock offers a unique set of features and benefits that make it a compelling choice for those looking to harness the power of generative AI. Here’s why you should consider using Amazon Bedrock:

  • Diverse Foundation Model Selection: Bedrock provides a streamlined developer interface to engage with a vast array of top-tier Foundation Models (FMs) from not only Amazon but also renowned AI entities such as AI21 Labs, Anthropic, Cohere, Meta, and Stability AI. This allows for swift experimentation in the playground and the convenience of a unified API for inference. This design ensures adaptability with models from various sources and facilitates seamless updates to the latest model iterations with minimal code adjustments.
  • Effortless Model Personalization: Bedrock empowers you to tailor FMs with your proprietary data through an intuitive visual platform, eliminating the need for coding. Simply designate the training and validation datasets located in Amazon S3, and if necessary, tweak the hyperparameters to optimize model efficacy.
  • Autonomous Agents with Dynamic API Invocation: Construct agents capable of managing intricate business operations, ranging from travel arrangements and insurance claim processing to ad campaign creation, tax preparation, and inventory management. These agents, backed by Bedrock, enhance the analytical prowess of FMs by segmenting tasks, formulating an orchestration strategy, and implementing it.
  • Inherent Retrieval Augmentation with RAG: Bedrock’s Knowledge Bases allow for a secure integration of FMs with your data repositories, offering retrieval augmentation directly within the managed service. This not only amplifies the inherent capabilities of the FMs but also enriches them with domain-specific knowledge pertinent to your organization.
  • Upholding Data Integrity and Regulatory Compliance: Bedrock prioritizes data security and has secured certifications for HIPAA eligibility and GDPR adherence. With Bedrock, the enhancement of base models doesn’t utilize your content, and no data is relayed to third-party model vendors. All data within Bedrock is encrypted both in transit and when stored, with an added option to use custom encryption keys. For enhanced security, AWS PrivateLink can be used with Bedrock to ensure private connectivity between your FMs and your Amazon VPC, keeping your data traffic away from public internet exposure.
  • Scalability and Flexibility: As businesses grow and evolve, so do their data needs. Bedrock is designed to scale with your requirements, ensuring that as your data volume or complexity increases, the platform can handle it without compromising performance.
  • Integrated Ecosystem: Bedrock seamlessly integrates with other AWS services, ensuring that you can build comprehensive solutions that leverage the broader AWS ecosystem. This integration ensures that data flow, processing, and storage are cohesive and efficient across the board.
  • Availability: As of October 10, 2023, AWS Bedrock has expanded its reach and is now available in three global regions: US East (N. Virginia), US West (Oregon), and Asia Pacific (Tokyo).

Agents for Amazon Bedrock: Simplifying Generative AI Apps

Generative AI applications have the potential to revolutionize industries by automating complex tasks and delivering up-to-date, accurate answers. However, the development of these applications often requires intricate orchestration and integration with various data sources. Amazon Bedrock introduces “Agents” to address these challenges and simplify the development process.

What are Agents for Amazon Bedrock?

Agents for Amazon Bedrock are fully managed capabilities designed to streamline the creation of generative AI-based applications. These agents are equipped to handle a wide range of use cases and can deliver precise answers based on proprietary knowledge sources.

Key Features of Agents:

  • Task Breakdown and Orchestration: With just a few clicks, agents automatically dissect tasks and devise an orchestration plan, eliminating the need for manual coding.
  • Seamless Data Integration: Agents can securely connect to company data through APIs, ensuring that data is automatically converted into a machine-readable format. This integration ensures that the AI models have access to the most relevant and up-to-date information, enhancing the accuracy of the generated response.
  • API Calls for Task Fulfillment: Once the data is processed and the AI models generate a response, agents can automatically call APIs to fulfill a user’s request. This automation ensures a seamless user experience and timely delivery of results.

Use Cases of Agents:

  • Healthcare Application: Imagine a large hospital network wanting to optimize patient care and resource allocation. They desire a system that can predict patient inflow, monitor equipment usage, track bed availability, and forecast staffing needs based on historical data and real-time inputs. By deploying agents for Amazon Bedrock, the hospital can create a dynamic system. These agents can integrate with electronic health records, monitor real-time patient admissions, and use generative AI to predict and recommend optimal resource distribution, ensuring timely care and efficient hospital operations.
  • Financial Services Application: Consider a global investment bank looking to enhance its trading strategies and risk management. They need a solution that can analyze vast amounts of financial data, track global market trends, and predict potential market shifts. Using Amazon Bedrock agents, the bank can build a system that autonomously monitors multiple data streams, from stock prices to geopolitical events. The agents can then generate predictive insights, helping traders make informed decisions and the bank to manage risks proactively.
  • Retail and E-commerce Application: Visualize a large e-commerce platform aiming to personalize the shopping experience for its millions of users. They want a system that can analyze user behavior, track product trends, monitor inventory, and dynamically adjust marketing strategies. By leveraging agents for Amazon Bedrock, the platform can develop an AI-driven system. These agents can integrate with user profiles, shopping histories, and real-time browsing data. They can then generate personalized product recommendations, optimize marketing campaigns, and even predict upcoming product trends, enhancing user engagement and boosting sales.
  • Manufacturing Inventory: Consider a manufacturing company aiming to harness the power of generative AI. They want an application that can autonomously track inventory levels, analyze sales data, monitor supply chain information, and recommend optimal reorder points and quantities to boost efficiency. Using agents for Amazon Bedrock, this company can easily develop such an application. The agents will handle the complex task of integrating with various data sources, processing the data, and generating actionable insights.

Architecture of Mediverse Bot using AWS Bedrock

While deploying & managing LLMs via SageMaker Jumpstart gives fine grained control over the FMs, Amazon Bedrock takes care of “undifferentiated heavy lifting” associated with system integration and infrastructure provisioning. Developers no longer need to worry about the intricacies of backend management and can instead focus on leveraging generative AI to its fullest potential across their organization.

Before vs After AWS Bedrock:

Mediverse Bot Integration with AWS Bedrock

AWS Lambda in the above architecture acts as a RAG proxy that queries internal FAISS Vector DB to identify relevant documents and also performs vector embedding on the user questions. The deployed Lambda is a Docker container based on Python 3.11 and uses Anthropic Claude V2 FM Bedrock endpoint.

Note: As of this writing, Lambda has older version of Boto3 that doesn’t have support for Bedrock. The requirements.txt file uses Boto3 1.28.57 that supports Bedrock client and runtime libraries.


In the rapidly evolving landscape of artificial intelligence, Amazon Bedrock emerges as a transformative force, especially in the realm of generative AI. It’s not just a tool but a comprehensive ecosystem that empowers businesses across various industries to harness the power of advanced AI models without the complexities traditionally associated with such cutting-edge technologies. From healthcare and finance to manufacturing and e-commerce, organizations can now build more intelligent, efficient, and innovative solutions. The integration of Bedrock into operational workflows signifies a leap towards a future where AI is not a mere facilitator but a strategic partner capable of driving significant advancements.

As we stand on the brink of this new era, it’s crucial for businesses to recognize the potential of services like Amazon Bedrock. It’s not only about the optimization of existing processes but also about pioneering new pathways that were previously inconceivable. By democratizing access to powerful generative AI, Bedrock is leveling the playing field, enabling entities of all sizes to dream big and innovate freely. The future promises a symbiosis between human ingenuity and artificial intelligence, forging a world where the combined potential can solve some of our most significant challenges and propel us into a new age of discovery and prosperity.


Author: Raghavan Madabusi