Artificial Intelligence

Category: Database

Streamline access to ISO-rating content changes with Verisk rating insights and Amazon Bedrock

In this post, we dive into how Verisk Rating Insights, powered by Amazon Bedrock, large language models (LLM), and Retrieval Augmented Generation (RAG), is transforming the way customers interact with and access ISO ERC changes.

Enterprise HR system architecture with ProfileMap centrally connecting four key modules for comprehensive workforce management

How msg enhanced HR workforce transformation with Amazon Bedrock and msg.ProfileMap

In this post, we share how msg automated data harmonization for msg.ProfileMap, using Amazon Bedrock to power its large language model (LLM)-driven data enrichment workflows, resulting in higher accuracy in HR concept matching, reduced manual workload, and improved alignment with compliance requirements under the EU AI Act and GDPR.

The power of AI in driving personalized product discovery at Snoonu

In this post, we share how Snoonu, a leading ecommerce platform in the Middle East, transformed their product discovery experience using AI-powered personalization. In this post, we share how Snoonu, a leading ecommerce platform in the Middle East, transformed their product discovery experience using AI-powered personalization.

Build a scalable containerized web application on AWS using the MERN stack with Amazon Q Developer – Part 1

In a traditional SDLC, a lot of time is spent in the different phases researching approaches that can deliver on requirements: iterating over design changes, writing, testing and reviewing code, and configuring infrastructure. In this post, you learned about the experience and saw productivity gains you can realize by using Amazon Q Developer as a coding assistant to build a scalable MERN stack web application on AWS.

Architecture diagram of the solution

Build a conversational data assistant, Part 1: Text-to-SQL with Amazon Bedrock Agents

In this post, we focus on building a Text-to-SQL solution with Amazon Bedrock, a managed service for building generative AI applications. Specifically, we demonstrate the capabilities of Amazon Bedrock Agents. Part 2 explains how we extended the solution to provide business insights using Amazon Q in QuickSight, a business intelligence assistant that answers questions with auto-generated visualizations.

Accelerating AI innovation: Scale MCP servers for enterprise workloads with Amazon Bedrock

In this post, we present a centralized Model Context Protocol (MCP) server implementation using Amazon Bedrock that provides shared access to tools and resources for enterprise AI workloads. The solution enables organizations to accelerate AI innovation by standardizing access to resources and tools through MCP, while maintaining security and governance through a centralized approach.

Solution Diagram

Building a custom text-to-SQL agent using Amazon Bedrock and Converse API

Developing robust text-to-SQL capabilities is a critical challenge in the field of natural language processing (NLP) and database management. The complexity of NLP and database management increases in this field, particularly while dealing with complex queries and database structures. In this post, we introduce a straightforward but powerful solution with accompanying code to text-to-SQL using a custom agent implementation along with Amazon Bedrock and Converse API.

Build conversational interfaces for structured data using Amazon Bedrock Knowledge Bases

This post provides instructions to configure a structured data retrieval solution, with practical code examples and templates. It covers implementation samples and additional considerations, empowering you to quickly build and scale your conversational data interfaces.