AWS Database Blog
Category: Generative AI
Build a scalable, context-aware chatbot with Amazon DynamoDB, Amazon Bedrock, and LangChain
Amazon DynamoDB, Amazon Bedrock, and LangChain can provide a powerful combination for building robust, context-aware chatbots. In this post, we explore how to use LangChain with DynamoDB to manage conversation history and integrate it with Amazon Bedrock to deliver intelligent, contextually aware responses. We break down the concepts behind the DynamoDB chat connector in LangChain, discuss the advantages of this approach, and guide you through the essential steps to implement it in your own chatbot.
Build a FedRAMP compliant generative AI-powered chatbot using Amazon Aurora Machine Learning and Amazon Bedrock
In this post, we explore how to use Amazon Aurora PostgreSQL and Amazon Bedrock to build Federal Risk and Authorization Management Program (FedRAMP) compliant generative artificial intelligence (AI) applications using Retrieval Augmented Generation (RAG).
How LeadSquared accelerated chatbot deployments with generative AI using Amazon Bedrock and Amazon Aurora PostgreSQL
LeadSquared is a new-age software as a service (SaaS) customer relationship management (CRM) platform that provides end-to-end sales, marketing, and onboarding solutions. Tailored for sectors like BFSI (banking, financial services, and insurance), healthcare, education, real estate, and more, LeadSquared provides a personalized approach for businesses of every scale. LeadSquared Service CRM goes beyond basic ticketing, […]
Optimize generative AI applications with pgvector indexing: A deep dive into IVFFlat and HNSW techniques
In recent times, there has been a growing interest in using foundation models (FMs) to build generative AI applications. These models are trained on vast amounts of data and are capable of performing tasks that were previously thought to be the exclusive domain of humans, such as creating art and music. However, when it comes […]
Improve the performance of generative AI workloads on Amazon Aurora with Optimized Reads and pgvector
Generative AI has increased the possibilities for businesses to build applications that require searching and comparison of unstructured data types such as text, images, and video. Embeddings, or vectors, capture the meaning and context of this unstructured data in a machine-readable form, which is the basis for how similarity comparisons can be made directly in […]
Diagram-as-code using generative AI to build a data model for Amazon Neptune
To be successful with a graph database—such as Amazon Neptune, a managed graph database service—you need a graph data model that captures the data you need and can answer your questions efficiently. Building that model is an iterative process. The earliest stage of the process, in which you are merely getting initial elements on paper […]
Build a generative AI-powered agent assistance application using Amazon Aurora and Amazon SageMaker JumpStart
Generative AI is a form of artificial intelligence (AI) that is designed to generate content, including text, images, video, and music. In today’s business landscape, harnessing the potential of generative AI has become essential to remain competitive. Foundation models are a form of generative AI. They generate output from one or more inputs (prompts) in […]
Revolutionize retail recommendations for ecommerce with Amazon RDS for PostgreSQL and generative AI
In today’s digital age, ecommerce has become an integral part of our lives, offering convenience and endless product options at our fingertips. To enhance online shopping experience, retailers use personalized product recommendations as a key strategy to engage customers and boost sales. Among the cutting-edge technologies fueling this revolution is the vector database, a powerful […]
Leverage pgvector and Amazon Aurora PostgreSQL for Natural Language Processing, Chatbots and Sentiment Analysis
March 2024: This post was reviewed and updated to include Amazon Bedrock models (Titan and Anthropic Claude). Generative AI – a category of artificial intelligence algorithms that can generate new content based on existing data — has been hailed as the next frontier for various industries, from tech to financial services, e-commerce and healthcare. And […]