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 226

Customer Experience Customer Support Customer Service Technology 226

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 119

APIs Accountability Enterprise Engineering 119

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 129

APIs Enterprise Automotive Customer Support 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 110

Education Engineering APIs Enterprise 110

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 117

Best practices Enterprise Engineering Strategic Value 117

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 108

Accountability Sales CRM APIs 108

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 383

Customer Service Chatbots Accountability Self service 383

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

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 130

APIs Transportation Best practices Enterprise 130

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 378

Customer Service Chatbots Education Feedback 378

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 112

APIs Best practices Management Personalization 112

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 108

Sales Accountability APIs CRM 108

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

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 117

Construction APIs Metrics Accountability 117

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 100

Enterprise Engineering APIs Best practices 100

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 112

Engineering Metrics industry standards Finance 112

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 113

Healthcare Analytics Consulting Consulting 113

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 92

Chatbots Metrics Scripts APIs 92

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 117

Metrics Enterprise APIs Engineering 117

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

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 112

APIs Automotive Accountability Analytics 112

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 106

Government Enterprise Wait times Engineering 106

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 107

Benchmark APIs Enterprise Construction 107

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 108

Sales APIs Engineering Analytics 108

AWS Machine Learning

FEBRUARY 19, 2025

To use Automated Reasoning checks, you first create an Automated Reasoning policy by encoding a set of logical rules and variables from available source documentation. Automated Reasoning checks deliver deterministic verification of model outputs against documented rules, complete with audit trails and mathematical proof of policy adherence.

APIs 84

APIs Banking Engineering Transportation 84

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 113

Best practices Feedback Metrics APIs 113

AWS Machine Learning

FEBRUARY 25, 2025

This post shows how to configure an Amazon Q Business custom connector and derive insights by creating a generative AI-powered conversation experience on AWS using Amazon Q Business while using access control lists (ACLs) to restrict access to documents based on user permissions. Who are the data stewards for my proprietary database sources?

Enterprise 102

Enterprise Engineering APIs Accountability 102

AWS Machine Learning

FEBRUARY 12, 2025

Your task is to understand a system that takes in a list of documents, and based on that, answers a question by providing citations for the documents that it referred the answer from. Our dataset includes Q&A pairs with reference documents regarding AWS services. The following table shows an example.

APIs 75

APIs Management Benchmark Scripts 75

AWS Machine Learning

NOVEMBER 26, 2024

Solution overview In this post, we demonstrate how to use models on Amazon Bedrock to retrieve information from images, tables, and scanned documents. This is one of the documents that a customer seeking a loan has uploaded. Identify what the class of this document is and give me just the class name.

Real estate 106

Real estate Engineering APIs Advertising 106