AWS Machine Learning - AI

OCTOBER 31, 2024

By implementing this architectural pattern, organizations that use Google Workspace can empower their workforce to access groundbreaking AI solutions powered by Amazon Web Services (AWS) and make informed decisions without leaving their collaboration tool. In the following sections, we explain how to deploy this architecture.

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AWS Machine Learning - AI

FEBRUARY 29, 2024

Knowledge Bases for Amazon Bedrock allows you to build performant and customized Retrieval Augmented Generation (RAG) applications on top of AWS and third-party vector stores using both AWS and third-party models. If you want more control, Knowledge Bases lets you control the chunking strategy through a set of preconfigured options.

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AWS Machine Learning - AI

SEPTEMBER 25, 2024

Amazon Bedrock Knowledge Bases is a fully managed capability that helps you implement the entire RAG workflow—from ingestion to retrieval and prompt augmentation—without having to build custom integrations to data sources and manage data flows. Latest innovations in Amazon Bedrock Knowledge Base provide a resolution to this issue.

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AWS Machine Learning - AI

DECEMBER 4, 2024

The following diagram illustrates the conceptual architecture of an AI assistant with Amazon Bedrock IDE. Solution architecture The architecture in the preceding figure shows how Amazon Bedrock IDE orchestrates the data flow. Choose Create new Knowledge Base and enter a name for your new knowledge base.

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AWS Machine Learning - AI

OCTOBER 29, 2024

We have built a custom observability solution that Amazon Bedrock users can quickly implement using just a few key building blocks and existing logs using FMs, Amazon Bedrock Knowledge Bases , Amazon Bedrock Guardrails , and Amazon Bedrock Agents. versions, catering to different programming preferences.

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AWS Machine Learning - AI

MARCH 20, 2025

With Amazon Bedrock Data Automation, enterprises can accelerate AI adoption and develop solutions that are secure, scalable, and responsible. By converting unstructured document collections into searchable knowledge bases, organizations can seamlessly find, analyze, and use their data.

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AWS Machine Learning - AI

JANUARY 29, 2025

In this post, we evaluate different generative AI operating model architectures that could be adopted. Generative AI architecture components Before diving deeper into the common operating model patterns, this section provides a brief overview of a few components and AWS services used in the featured architectures.

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AWS Machine Learning - AI

DECEMBER 11, 2024

When Amazon Q Business became generally available in April 2024, we quickly saw an opportunity to simplify our architecture, because the service was designed to meet the needs of our use caseto provide a conversational assistant that could tap into our vast (sales) domain-specific knowledge bases.

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AWS Machine Learning - AI

DECEMBER 4, 2024

Organizations can use these models securely, and for models that are compatible with the Amazon Bedrock Converse API, you can use the robust toolkit of Amazon Bedrock, including Amazon Bedrock Agents , Amazon Bedrock Knowledge Bases , Amazon Bedrock Guardrails , and Amazon Bedrock Flows.

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AWS Machine Learning - AI

JANUARY 29, 2025

Accelerate your generative AI application development by integrating your supported custom models with native Bedrock tools and features like Knowledge Bases, Guardrails, and Agents. The resulting distilled models, such as DeepSeek-R1-Distill-Llama-8B (from base model Llama-3.1-8B 8B 128K model to 8 Units for a Llama 3.1

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CIO

NOVEMBER 1, 2024

As part of MMTech’s unifying strategy, Beswick chose to retire the data centers and form an “enterprisewide architecture organization” with a set of standards and base layers to develop applications and workloads that would run on the cloud, with AWS as the firm’s primary cloud provider. The biggest challenge is data.

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AWS Machine Learning - AI

APRIL 10, 2025

They offer fast inference, support agentic workflows with Amazon Bedrock Knowledge Bases and RAG, and allow fine-tuning for text and multi-modal data. To do so, we create a knowledge base. Complete the following steps: On the Amazon Bedrock console, choose Knowledge Bases in the navigation pane.

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AWS Machine Learning - AI

NOVEMBER 1, 2024

Organizations need to prioritize their generative AI spending based on business impact and criticality while maintaining cost transparency across customer and user segments. This visibility is essential for setting accurate pricing for generative AI offerings, implementing chargebacks, and establishing usage-based billing models.

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AWS Machine Learning - AI

NOVEMBER 6, 2024

Limited scalability – As the volume of requests increased, the CCoE team couldn’t disseminate updated directives quickly enough. Going forward, the team enriched the knowledge base (S3 buckets) and implemented a feedback loop to facilitate continuous improvement of the solution.

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AWS Machine Learning - AI

NOVEMBER 15, 2024

As Principal grew, its internal support knowledge base considerably expanded. With QnABot, companies have the flexibility to tier questions and answers based on need, from static FAQs to generating answers on the fly based on documents, webpages, indexed data, operational manuals, and more.

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CIO

NOVEMBER 1, 2024

As part of MMTech’s unifying strategy, Beswick chose to retire the data centers and form an “enterprisewide architecture organization” with a set of standards and base layers to develop applications and workloads that would run on the cloud, with AWS as the firm’s primary cloud provider. The biggest challenge is data.

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AWS Machine Learning - AI

MARCH 20, 2025

The Asure team was manually analyzing thousands of call transcripts to uncover themes and trends, a process that lacked scalability. Staying ahead in this competitive landscape demands agile, scalable, and intelligent solutions that can adapt to changing demands.

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AWS Machine Learning - AI

SEPTEMBER 24, 2024

It’s a fully serverless architecture that uses Amazon OpenSearch Serverless , which can run petabyte-scale workloads, without you having to manage the underlying infrastructure. The following diagram illustrates the solution architecture. This solution uses Amazon Bedrock LLMs to find answers to questions from your knowledge base.

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AWS Machine Learning - AI

MARCH 20, 2025

It integrates with existing applications and includes key Amazon Bedrock features like foundation models (FMs), prompts, knowledge bases, agents, flows, evaluation, and guardrails. Before we dive deep into the deployment of the AI agent, lets walk through the key steps of the architecture, as shown in the following diagram.

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AWS Machine Learning - AI

NOVEMBER 20, 2024

In this post, we explore how you can use Amazon Q Business , the AWS generative AI-powered assistant, to build a centralized knowledge base for your organization, unifying structured and unstructured datasets from different sources to accelerate decision-making and drive productivity.

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AWS Machine Learning - AI

MARCH 7, 2025

In this post, we describe the development journey of the generative AI companion for Mozart, the data, the architecture, and the evaluation of the pipeline. The following diagram illustrates the solution architecture. You can create a decoupled architecture with reusable components. Connect with him on LinkedIn.

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AWS Machine Learning - AI

NOVEMBER 7, 2024

Depending on the use case and data isolation requirements, tenants can have a pooled knowledge base or a siloed one and implement item-level isolation or resource level isolation for the data respectively. You can also bring your own customized models and deploy them to Amazon Bedrock for supported architectures.

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AWS Machine Learning - AI

JULY 11, 2024

This solution shows how Amazon Bedrock agents can be configured to accept cloud architecture diagrams, automatically analyze them, and generate Terraform or AWS CloudFormation templates. Solution overview Before we explore the deployment process, let’s walk through the key steps of the architecture as illustrated in Figure 1.

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AWS Machine Learning - AI

SEPTEMBER 26, 2024

Although Amazon Q is a great way to get started with no code for business users, Amazon Bedrock Knowledge Bases offers more flexibility at the API level for generative AI developers; we explore both these solutions in the following sections. How do I keep my generative AI applications up to date with an ever-evolving knowledge base?”

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Perficient

JANUARY 9, 2025

Integration Capabilities MuleSoft’s Integration Capabilities Supports various integration patterns, including API-led integration, data integration, and event-driven architectures. The architecture supports microservices, enhancing scalability and performance. When there is a significant need for cloud-based integrations.

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AWS Machine Learning - AI

MARCH 18, 2025

If a user has a role configured with a specific guardrail requirement (using the bedrock:GuardrailIdentifier condition), they shouldnt use that same role to access services like Amazon Bedrock Knowledge Bases RetrieveAndGenerate or Amazon Bedrock Agents InvokeAgent.

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Cloudera

NOVEMBER 1, 2023

The AMP demonstrates how organizations can create a dynamic knowledge base from website data, enhancing the chatbot’s ability to deliver context-rich, accurate responses. An overview of the RAG architecture with a vector database used to minimize hallucinations in the chatbot application.

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AWS Machine Learning - AI

APRIL 24, 2024

It uses the provided conversation history, action groups, and knowledge bases to understand the context and determine the necessary tasks. This is based on the instructions that are interpreted by the assistant as per the system prompt and user’s input. Additionally, you can access device historical data or device metrics.

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AWS Machine Learning - AI

OCTOBER 15, 2024

By using Amazon Bedrock Agents , action groups , and Amazon Bedrock Knowledge Bases , we demonstrate how to build a migration assistant application that rapidly generates migration plans, R-dispositions, and cost estimates for applications migrating to AWS.

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AWS Machine Learning - AI

MAY 30, 2024

In this blog, we walkthrough the architectural components, evaluation criteria for the components selected by Vitech and the process flow of user interaction within VitechIQ. The following diagram shows the solution architecture. Continuous evolution and learning – Vitech is able to expand its knowledge base on new domains.

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AWS Machine Learning - AI

AUGUST 2, 2024

An approach to product stewardship with generative AI Large language models (LLMs) are trained with vast amounts of information crawled from the internet, capturing considerable knowledge from multiple domains. However, their knowledge is static and tied to the data used during the pre-training phase.

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AWS Machine Learning - AI

APRIL 29, 2025

The following diagram illustrates the solution architecture. For knowledge retrieval, we use Amazon Bedrock Knowledge Bases , which integrates with Amazon Simple Storage Service (Amazon S3) for document storage, and Amazon OpenSearch Serverless for rapid and scalable search capabilities.

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John Snow Labs

DECEMBER 13, 2024

John Snow Labs Generative AI platform can access, understand, and apply the latest evidence-based research from the most authoritative knowledge bases. This new AI solution is powered by John Snow Labs , the award-winning Healthcare AI company and the worlds leading provider of Medical Language Models.

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AWS Machine Learning - AI

MAY 13, 2024

To implement our RAG system, we utilized a dataset of 95,000 radiology report findings-impressions pairs as the knowledge source. This dataset was uploaded to Amazon Simple Service (Amazon S3) data source and then ingested using Knowledge Bases for Amazon Bedrock. client('bedrock-runtime') bedrock_agent_client = boto3.client("bedrock-agent-runtime",

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AWS Machine Learning - AI

FEBRUARY 25, 2025

Solution overview Before we dive into the deployment process, lets walk through the key steps of the architecture as illustrated in the following figure. By using the capabilities of Amazon Bedrock Agents, it offers a scalable and intelligent approach to managing IaC challenges in large, multi-account AWS environments.

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AWS Machine Learning - AI

MAY 9, 2024

Verisk’s FAST platform is a leader in the life insurance and retirement sector, providing enhanced efficiency and flexible, easily upgradable architecture. In this post, we describe the development of the customer support process in FAST incorporating generative AI, the data, the architecture, and the evaluation of the results.

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AWS Machine Learning - AI

DECEMBER 6, 2023

To create AI assistants that are capable of having discussions grounded in specialized enterprise knowledge, we need to connect these powerful but generic LLMs to internal knowledge bases of documents. Then we introduce you to a more versatile architecture that overcomes these limitations.

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