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Knowledge Bases in Amazon Bedrock now simplifies asking questions on a single document

AWS Machine Learning

With Knowledge Bases for Amazon Bedrock, you can securely connect foundation models (FMs) in Amazon Bedrock to your company data for fully managed Retrieval Augmented Generation (RAG). Today, we’re introducing the new capability to chat with your document with zero setup in Knowledge Bases for Amazon Bedrock.

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Empower your business users to extract insights from company documents using Amazon SageMaker Canvas Generative AI

AWS Machine Learning

For example, business teams can now formulate responses consistent with an organization’s specific vocabulary and tenets, and can more quickly query lengthy documents to get responses specific and grounded to the contents of those documents. We describe the set-up process in detail in Setting up Canvas to query documents.

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Accenture creates a regulatory document authoring solution using AWS generative AI services

AWS Machine Learning

Companies face complex regulations and extensive approval requirements from governing bodies like the US Food and Drug Administration (FDA). This document contains over 100 highly detailed technical reports created during the process of drug research and testing. AI delivers a major leap forward.

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Intelligent document processing with Amazon Textract, Amazon Bedrock, and LangChain

AWS Machine Learning

In today’s information age, the vast volumes of data housed in countless documents present both a challenge and an opportunity for businesses. Traditional document processing methods often fall short in efficiency and accuracy, leaving room for innovation, cost-efficiency, and optimizations. However, the potential doesn’t end there.

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Customer Success Needs to Grow (Up)

Speaker: Peter Armaly - Senior Director and Advisor of Customer Success at Oracle

Customer success is a well-established practice in the enterprise business world (70% of companies have a dedicated team, according to TSIA) and the benefits it delivers to customers are real and well-documented. Demand more accountability of the practice. Empirically tie CS activities to a real revenue impact.

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Automate chatbot for document and data retrieval using Agents and Knowledge Bases for Amazon Bedrock

AWS Machine Learning

This post presents a solution for developing a chatbot capable of answering queries from both documentation and databases, with straightforward deployment. For documentation retrieval, Retrieval Augmented Generation (RAG) stands out as a key tool. Virginia) AWS Region. The following diagram illustrates the solution architecture.

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Implement smart document search index with Amazon Textract and Amazon OpenSearch

AWS Machine Learning

For modern companies that deal with enormous volumes of documents such as contracts, invoices, resumes, and reports, efficiently processing and retrieving pertinent data is critical to maintaining a competitive edge. What if there was a way to process documents intelligently and make them searchable in with high accuracy?

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4 Strategies to Boost Agent Productivity

Speaker: Melissa Pollock, Customer Success Officer, AmplifAI

As companies continue to seek every competitive advantage available, organizations must explore new opportunities and ways to increase productivity in our modern contact centers. What to identify, document and share. In this webinar, you will know: How to build the necessary interpersonal skills to engender CX behaviors.

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The Health of the Contact Center: Are You Ready for 2019?

A survey of 1,000 contact center professionals reveals what it takes to improve agent well-being in a customer-centric era. This report is a must-read for contact center leaders preparing to engage agents and improve customer experience in 2019.