AWS Machine Learning

AUGUST 9, 2024

Question and answering (Q&A) using documents is a commonly used application in various use cases like customer support chatbots, legal research assistants, and healthcare advisors. In this collaboration, the AWS GenAIIC team created a RAG-based solution for Deltek to enable Q&A on single and multiple government solicitation documents.

Government 129

Government Healthcare Construction Engineering 129

ShepHyken

FEBRUARY 10, 2025

” “Your customers can now know more about your company than you do by using AI to scrape your website and documentation. If you had a magic wand, what would you want to do for your customers that you can’t do today? And, how can AI enable that?”

Customer Experience 230

Customer Experience Customer Support Customer Service Technology 230

Cincom

JANUARY 31, 2025

This is the scenario for companies that rely on manual processes for document generationcaught in a cycle of repetitive data entry, missing critical details, non-compliance, and whatnot. Every document you produce is an opportunity to reinforce your brands identity, tone, and professionalism. What is Document Generation Software?

CRM 40

CRM APIs industry standards Customer centricity 40

AWS Machine Learning

OCTOBER 31, 2024

Google Drive supports storing documents such as Emails contain a wealth of information found in different places, such as within the subject of an email, the message content, or even attachments. Types of documents Gmail messages can be sorted and stored inside your email inbox using folders and labels.

APIs 118

APIs Accountability Enterprise Engineering 118

AWS Machine Learning

NOVEMBER 7, 2024

Access to car manuals and technical documentation helps the agent provide additional context for curated guidance, enhancing the quality of customer interactions. The workflow includes the following steps: Documents (owner manuals) are uploaded to an Amazon Simple Storage Service (Amazon S3) bucket.

APIs 128

APIs Enterprise Automotive Customer Support 128

AWS Machine Learning

MARCH 4, 2025

We demonstrate how to harness the power of LLMs to build an intelligent, scalable system that analyzes architecture documents and generates insightful recommendations based on AWS Well-Architected best practices. An interactive chat interface allows deeper exploration of both the original document and generated content.

Best practices 112

Best practices Enterprise Engineering Strategic Value 112

AWS Machine Learning

NOVEMBER 15, 2024

Principal wanted to use existing internal FAQs, documentation, and unstructured data and build an intelligent chatbot that could provide quick access to the right information for different roles. For queries earning negative feedback, less than 1% involved answers or documentation deemed irrelevant to the original question.

Chatbots 113

Chatbots Engineering Enterprise Government 113

ShepHyken

JULY 2, 2021

Compile the most frequently asked questions in a shared document, determine the best possible answers, and distribute the document to your customer service team. . This document will act as a single source of truth your team can reference. Are you finding any patterns in questions or concerns stated over social media?

Customer Service 387

Customer Service Chatbots Accountability Self service 387

CCNG

OCTOBER 16, 2024

When designing a process, use the following steps to build something that is scalable: Create a simple flow chart that documents each step in the process. For each step, identify the following items: Systems needed. What computer systems are required? If there is a limit on how fast something can be processed, what is it?

CCNG 195

CCNG Construction Consulting Consulting 195

ShepHyken

NOVEMBER 20, 2020

The vision document is critical to set the direction for your team, so you need to make it clear. Also, make it available at all times through your company’s document sharing service. Include an explanation of each touchpoint in a separate document. Make it step-by-step to include every communication touchpoint.

Customer Service 382

Customer Service Chatbots Education Feedback 382

AWS Machine Learning

APRIL 23, 2025

RAG workflow: Converting data to actionable knowledge RAG consists of two major steps: Ingestion Preprocessing unstructured data, which includes converting the data into text documents and splitting the documents into chunks. Document chunks are then encoded with an embedding model to convert them to document embeddings.

APIs 89

APIs Healthcare Enterprise Accountability 89

AWS Machine Learning

JANUARY 22, 2025

The following is an example FlowMultiTurnInputRequestEvent JSON object: { "nodeName": "Trip_planner", "nodeType": "AgentNode", "content": { "document": "Certainly! The following is an example FlowOutputEvent JSON object: { "nodeName": "FlowOutputNode", "content": { "document": "Great news! I've successfully booked your flight to Paris.

APIs 129

APIs Transportation Best practices Enterprise 129

AWS Machine Learning

MARCH 27, 2025

Lets say the task at hand is to predict the root cause categories (Customer Education, Feature Request, Software Defect, Documentation Improvement, Security Awareness, and Billing Inquiry) for customer support cases. We suggest consulting LLM prompt engineering documentation such as Anthropic prompt engineering for experiments.

Education 109

Education Engineering APIs Enterprise 109

Beyond Philosophy

AUGUST 13, 2020

We changed the line the new policy representatives said from, “You should receive your policy documents in five working days,” to “You will receive your policy documents in five working days.”

Customer effort 457

Customer effort Government Consulting Consulting 457

AWS Machine Learning

APRIL 30, 2025

Similarly, when an incident occurs in IT, the responding team must provide a precise, documented history for future reference and troubleshooting. As businesses expand, they encounter a vast array of transactions that require meticulous documentation, categorization, and reconciliation.

Accountability 96

Accountability Banking Engineering Entertainment 96

AWS Machine Learning

DECEMBER 11, 2024

This enables sales teams to interact with our internal sales enablement collateral, including sales plays and first-call decks, as well as customer references, customer- and field-facing incentive programs, and content on the AWS website, including blog posts and service documentation.

Sales 104

Sales Accountability APIs CRM 104

AWS Machine Learning

MARCH 4, 2025

Amazon Bedrock Knowledge Bases has a metadata filtering capability that allows you to refine search results based on specific attributes of the documents, improving retrieval accuracy and the relevance of responses. Improving document retrieval results helps personalize the responses generated for each user.

APIs 106

APIs Best practices Management Personalization 106

AWS Machine Learning

APRIL 3, 2025

Every year, AWS Sales personnel draft in-depth, forward looking strategy documents for established AWS customers. These documents help the AWS Sales team to align with our customer growth strategy and to collaborate with the entire sales team on long-term growth ideas for AWS customers.

Accountability 103

Accountability Sales CRM APIs 103

AWS Machine Learning

NOVEMBER 20, 2024

By narrowing down the search space to the most relevant documents or chunks, metadata filtering reduces noise and irrelevant information, enabling the LLM to focus on the most relevant content. This approach narrows down the search space to the most relevant documents or passages, reducing noise and irrelevant information.

Construction 116

Construction APIs Metrics Accountability 116

AWS Machine Learning

APRIL 29, 2025

The following example shows how prompt optimization converts a typical prompt for a summarization task on Anthropics Claude Haiku into a well-structured prompt for an Amazon Nova model, with sections that begin with special markdown tags such as ## Task, ### Summarization Instructions , and ### Document to Summarize.

Metrics 81

Metrics Engineering Best practices Benchmark 81

AWS Machine Learning

JANUARY 7, 2025

The solution offers two TM retrieval modes for users to choose from: vector and document search. When using the Amazon OpenSearch Service adapter (document search), translation unit groupings are parsed and stored into an index dedicated to the uploaded file. For this post, we use a document store. Choose With Document Store.

Engineering 110

Engineering Metrics industry standards Finance 110

AWS Machine Learning

MARCH 18, 2025

Site monitors conduct on-site visits, interview personnel, and verify documentation to assess adherence to protocols and regulatory requirements. However, this process can be time-consuming and prone to errors, particularly when dealing with extensive audio recordings and voluminous documentation.

Healthcare 111

Healthcare Analytics Consulting Consulting 111

Beyond Philosophy

JUNE 11, 2020

We discovered that when customers ordered an insurance policy, the insurance agent would say, “your documentation should be with you within five working days.” ” It turns out the vast majority of people would call back within three days to ask about the documents after this interaction.

Wait times 403

Wait times Management Consulting Consulting 403

AWS Machine Learning

FEBRUARY 11, 2025

Large-scale data ingestion is crucial for applications such as document analysis, summarization, research, and knowledge management. These tasks often involve processing vast amounts of documents, which can be time-consuming and labor-intensive. This solution uses the powerful capabilities of Amazon Q Business.

Enterprise 94

Enterprise Engineering APIs Best practices 94

AWS Machine Learning

OCTOBER 24, 2024

Broadly speaking, a retriever is a module that takes a query as input and outputs relevant documents from one or more knowledge sources relevant to that query. Document ingestion In a RAG architecture, documents are often stored in a vector store. You must use the same embedding model at ingestion time and at search time.

Chatbots 90

Chatbots Metrics Scripts APIs 90

AWS Machine Learning

MARCH 6, 2025

Optimized for search and retrieval, it streamlines querying LLMs and retrieving documents. Build sample RAG Documents are segmented into chunks and stored in an Amazon Bedrock Knowledge Bases (Steps 24). For this purpose, LangChain provides a WebBaseLoader object to load text from HTML webpages into a document format.

Metrics 114

Metrics Enterprise APIs Engineering 114

AWS Machine Learning

MARCH 19, 2025

AWS customers and partners innovate using Amazon Q Business in Europe Organizations across the EU are using Amazon Q Business for a wide variety of use cases, including answering questions about company data, summarizing documents, and providing business insights. text, pdf, images, tables).

Government 104

Government Enterprise Wait times Engineering 104

AWS Machine Learning

MARCH 19, 2025

operation.font.set({ name: 'Arial' }); // flush changes to the Word document await context.sync(); }); Generative AI backend infrastructure The AWS Cloud backend consists of three components: Amazon API Gateway acts as an entry point, receiving requests from the Office applications Add-in. Here, we use Anthropics Claude 3.5

APIs 110

APIs Automotive Accountability Analytics 110

AWS Machine Learning

DECEMBER 3, 2024

Efficient metadata storage with Amazon DynamoDB – To support quick and efficient data retrieval, document metadata is stored in Amazon DynamoDB. Key components include: Orchestrated document processing with AWS Step Functions – The document processing workflow begins with AWS Step Functions , which orchestrates each step in the process.

Sales 107

Sales APIs Engineering Analytics 107

AWS Machine Learning

OCTOBER 29, 2024

For a detailed breakdown of the features and implementation specifics, refer to the comprehensive documentation in the GitHub repository. You can follow the steps provided in the Deleting a stack on the AWS CloudFormation console documentation to delete the resources created for this solution.

Best practices 112

Best practices Feedback Metrics APIs 112

AWS Machine Learning

MARCH 3, 2025

Designed for both image and document comprehension, Pixtral demonstrates advanced capabilities in vision-related tasks, including chart and figure interpretation, document question answering, multimodal reasoning, and instruction followingseveral of which are illustrated with examples later in this post. Pixtral_data/a01-000u-04.png'

Benchmark 101

Benchmark APIs Enterprise Construction 101