Inbenta

APRIL 29, 2020

Depending on the context in which the chatbot project takes place, and therefore its scope of action, its implementation may take more or less time. Indeed, the development of a chatbot implies creating new jobs such as the one of Botmaster for example. How long does it take to deploy an AI chatbot? Let’s see what these can be.

Chatbots 140

Chatbots APIs Construction Best practices 140

AWS Machine Learning

APRIL 26, 2024

At AWS re:Invent 2023, we announced the general availability of Knowledge Bases for Amazon Bedrock. 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).

APIs 127

APIs Enterprise Chatbots Engineering 127

AWS Machine Learning

APRIL 23, 2024

This post explores the new enterprise-grade features for Knowledge Bases on Amazon Bedrock and how they align with the AWS Well-Architected Framework. AWS Well-Architected design principles RAG-based applications built using Knowledge Bases for Amazon Bedrock can greatly benefit from following the AWS Well-Architected Framework.

APIs 127

APIs Enterprise Scripts Accountability 127

AWS Machine Learning

APRIL 8, 2024

At AWS re:Invent 2023, we announced the general availability of Knowledge Bases for Amazon Bedrock. With Knowledge Bases for Amazon Bedrock, you can securely connect foundation models (FMs) in Amazon Bedrock to your company data using a fully managed Retrieval Augmented Generation (RAG) model.

APIs 132

APIs Construction Chatbots Accountability 132

AWS Machine Learning

NOVEMBER 15, 2024

As Principal grew, its internal support knowledge base considerably expanded. 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.

Chatbots 114

Chatbots Engineering Enterprise Government 114

AWS Machine Learning

AUGUST 5, 2024

Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies through a single API, along with a broad set of capabilities to build generative AI applications with security, privacy, and responsible AI. Included with Amazon Bedrock is Knowledge Bases for Amazon Bedrock.

APIs 118

APIs Engineering Chatbots Management 118

AWS Machine Learning

APRIL 10, 2025

They offer fast inference, support agentic workflows with Amazon Bedrock Knowledge Bases and RAG, and allow fine-tuning for text and multi-modal data. To do so, we create a knowledge base. Complete the following steps: On the Amazon Bedrock console, choose Knowledge Bases in the navigation pane. Choose Next.

APIs 125

APIs Metrics Best practices Construction 125

AWS Machine Learning

DECEMBER 11, 2024

Document upload When users need to provide context of their own, the chatbot supports uploading multiple documents during a conversation. We deliver our chatbot experience through a custom web frontend, as well as through a Slack application. Previously, we had to build and maintain custom logic to handle these tasks.

Sales 110

Sales Accountability APIs CRM 110

AWS Machine Learning

SEPTEMBER 13, 2024

Intricate workflows that require dynamic and complex API orchestration can often be complex to manage. In this post, we explore how chaining domain-specific agents using Amazon Bedrock Agents can transform a system of complex API interactions into streamlined, adaptive workflows, empowering your business to operate with agility and precision.

APIs 133

APIs Enterprise Best practices Accountability 133

AWS Machine Learning

MARCH 6, 2025

Amazon Bedrock is a fully managed service that offers a choice of high-performing Foundation Models (FMs) from leading AI companies like AI21 Labs, Anthropic, Cohere, Meta, Stability AI, and Amazon via a single API, along with a broad set of capabilities you need to build generative AI applications with security, privacy, and responsible AI.

Metrics 120

Metrics Enterprise APIs Engineering 120

AWS Machine Learning

FEBRUARY 18, 2025

During these live events, F1 IT engineers must triage critical issues across its services, such as network degradation to one of its APIs. This impacts downstream services that consume data from the API, including products such as F1 TV, which offer live and on-demand coverage of every race as well as real-time telemetry.

APIs 71

APIs Engineering Metrics Big data 71

AWS Machine Learning

AUGUST 15, 2024

QnABot on AWS (an AWS Solution) now provides access to Amazon Bedrock foundational models (FMs) and Knowledge Bases for Amazon Bedrock , a fully managed end-to-end Retrieval Augmented Generation (RAG) workflow. After authentication, Amazon API Gateway and Amazon S3 deliver the contents of the Content Designer UI.

Chatbots 127

Chatbots Banking APIs Enterprise 127

AWS Machine Learning

MAY 30, 2024

Amazon Bedrock is a fully managed service that makes FMs from leading AI startups and Amazon available via an API, so one can choose from a wide range of FMs to find the model that is best suited for their use case. However, for this use case, the complexity associated with fine-tuning and the costs were not warranted.

Chatbots 132

Chatbots Engineering APIs Technology 132

Netomi

SEPTEMBER 20, 2021

Chatbots are used by 1.4 Companies are launching their best AI chatbots to carry on 1:1 conversations with customers and employees. AI powered chatbots are also capable of automating various tasks, including sales and marketing, customer service, and administrative and operational tasks. What is an AI chatbot?

Chatbots 126

Chatbots APIs Surveys Analytics 126

AWS Machine Learning

OCTOBER 24, 2024

Since the inception of AWS GenAIIC in May 2023, we have witnessed high customer demand for chatbots that can extract information and generate insights from massive and often heterogeneous knowledge bases. a) to augment its knowledge, along with the user query (3.b). The following is a general diagram of a RAG workflow.

Chatbots 94

Chatbots Metrics Scripts APIs 94

AWS Machine Learning

SEPTEMBER 20, 2024

Amazon Bedrock agents use LLMs to break down tasks, interact dynamically with users, run actions through API calls, and augment knowledge using Amazon Bedrock Knowledge Bases. Dynamic information retrieval – Amazon Bedrock agents can use web search APIs to fetch up-to-date information on a wide range of topics.

APIs 106

APIs Chatbots Construction Engineering 106

AWS Machine Learning

NOVEMBER 15, 2024

In Part 1 of this series, we defined the Retrieval Augmented Generation (RAG) framework to augment large language models (LLMs) with a text-only knowledge base. A chatbot enables field engineers to quickly access relevant information, troubleshoot issues more effectively, and share knowledge across the organization.

APIs 118

APIs Engineering Chatbots Construction 118

AWS Machine Learning

JANUARY 31, 2024

By combining embeddings that capture semantics with a technique called Retrieval Augmented Generation (RAG) , you can generate more relevant answers based on retrieved context from your own data sources. Create a knowledge base. Sync your knowledge base with your data source.

Chatbots 125

Chatbots Entertainment Advertising APIs 125

Inbenta

JULY 2, 2018

Chatbots are a time-saving resource for internal employees whose energy is better spent on meaningful work and productivity. Internal chatbots have the potential to boost accessibility, efficiency, and employee satisfaction in your workplace. Chatbots are easy to use, setup, and deploy. Chatbots streamlining HR support.

Chatbots 110

Chatbots APIs Engineering Customer Support 110

AWS Machine Learning

SEPTEMBER 26, 2024

This post shows how aerospace customers can use AWS generative AI and ML-based services to address this document-based knowledge use case, using a Q&A chatbot to provide expert-level guidance to technical staff based on large libraries of technical documents. Avoiding the well-known problem of hallucination.)

APIs 119

APIs Chatbots Engineering Accountability 119

AWS Machine Learning

NOVEMBER 19, 2024

This chalk talk demonstrates how to process machine-generated signals into your contact center, allowing your knowledge base to provide real-time solutions. This includes Amazon Bedrock Guardrails, Agents, and Knowledge Bases, along with the creation of custom models.

APIs 109

APIs Enterprise Best practices Government 109

AWS Machine Learning

JULY 10, 2024

You can use the Prompt Management and Flows features graphically on the Amazon Bedrock console or Amazon Bedrock Studio, or programmatically through the Amazon Bedrock SDK APIs. Alternatively, you can use the CreateFlow API for a programmatic creation of flows that help you automate processes and development pipelines.

Management 134

Management APIs Chatbots Best practices 134

AWS Machine Learning

JUNE 12, 2023

OpenChatKit is an open-source LLM used to build general-purpose and specialized chatbot applications, released by Together Computer in March 2023 under the Apache-2.0 This model allows developers to have more control over the chatbot’s behavior and tailor it to their specific applications.

Chatbots 98

Chatbots APIs Engineering Enterprise 98

AWS Machine Learning

MARCH 18, 2025

Solution overview This solution is primarily based on the following services: Foundational model We use Anthropics Claude 3.5 These logs can be used to test the accuracy and enhance the context by providing more details in the knowledge base. streamlit run app.py About the Author Rajendra Choudhary is a Sr.

Enterprise 110

Enterprise Chatbots Engineering Metrics 110

AWS Machine Learning

OCTOBER 1, 2024

Specifically, we focus on chatbots. Chatbots are no longer a niche technology. Although AI chatbots have been around for years, recent advances of large language models (LLMs) like generative AI have enabled more natural conversations. We also provide a sample chatbot application. We discuss this later in the post.

Chatbots 92

Chatbots APIs Scripts Management 92

AWS Machine Learning

AUGUST 2, 2024

An approach to product stewardship with generative AI Large language models (LLMs) are trained with vast amounts of information crawled from the internet, capturing considerable knowledge from multiple domains. However, their knowledge is static and tied to the data used during the pre-training phase.

APIs 128

APIs Analytics Chatbots Engineering 128

AWS Machine Learning

MARCH 19, 2024

With Knowledge Bases for Amazon Bedrock , you can simplify the RAG development process to provide more accurate anomaly root cause analysis for plant workers. The user can use the Amazon Recognition DetectText API to extract text data from these images. Next, you create the knowledge base for the documents in Amazon S3.

Construction 137

Construction Scripts APIs Enterprise 137

Inbenta

JUNE 1, 2021

Summary: Use Cases of AI Chatbots for Internal Employees. Chatbots Streamline HR Support. Chatbots Facilitate Employee Onboarding. Chatbots Help With Day-to-Day Tasks. Chatbots Prove the Source of Truth: From Taxes to GDPR. Chatbots Empower Physical Robots. Chatbots are easy to use, setup, and deploy.

Chatbots 83

Chatbots APIs Engineering Customer Support 83

AWS Machine Learning

NOVEMBER 22, 2023

The LLM generated text, and the IR system retrieves relevant information from a knowledge base. In this post, we explore building a contextual chatbot for financial services organizations using a RAG architecture with the Llama 2 foundation model and the Hugging Face GPTJ-6B-FP16 embeddings model, both available in SageMaker JumpStart.

Engineering 126

Engineering Chatbots Benchmark APIs 126

JivoChat

APRIL 23, 2023

Chatbots have become a success around the world, and nowadays are used by 58% of B2B companies and 42% of B2C companies. In 2022 at least 88% of users had one conversation with chatbots. There are many reasons for that, a chatbot is able to simulate human interaction and provide customer service 24h a day. What Is a Chatbot?

Chatbots 75

Chatbots B2C Self service B2B 75

AWS Machine Learning

DECEMBER 13, 2024

In this post, we demonstrate how we innovated to build a Retrieval Augmented Generation (RAG) application with agentic workflow and a knowledge base on Amazon Bedrock. We implemented the RAG pipeline in a Slack chat-based assistant to empower the Amazon Twitch ads sales team to move quickly on new sales opportunities.

Sales 104

Sales Advertising Engineering APIs 104

Inbenta

AUGUST 30, 2021

Botium automates chatbot testing to boost the customer experience, cover all quality standards, meaning functional as well as non-functional testing. The Inbenta connector enables Inbenta users to test the following aspects of their chatbot: Regression Testing. The first step is to push the register new chatbot button in Botium Box.

Chatbots 59

Chatbots APIs Customer Experience Technology 59

AWS Machine Learning

AUGUST 30, 2023

Powered by Amazon Lex , the QnABot on AWS solution is an open-source, multi-channel, multi-language conversational chatbot. This includes automatically generating accurate answers from existing company documents and knowledge bases, and making their self-service chatbots more conversational.

Self service 132

Self service APIs Transportation Contact Center 132

AWS Machine Learning

MARCH 14, 2024

Whether creating a chatbot or summarization tool, you can shape powerful FMs to suit your needs. Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies like AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, Stability AI, and Amazon via a single API.

Best practices 136

Best practices Engineering Chatbots Enterprise 136

AWS Machine Learning

MAY 14, 2024

The entire conversation in this use case, starting with generative AI and then bringing in human agents who take over, is logged so that the interaction can be used as part of the knowledge base. We built the RAG solution as detailed in the following GitHub repo and used SageMaker documentation as the knowledge base.

Chatbots 122

Chatbots Feedback Engineering Entertainment 122

AWS Machine Learning

SEPTEMBER 20, 2024

There are many challenges that can impact employee productivity, such as cumbersome search experiences or finding specific information across an organization’s vast knowledge bases. Knowledge management: Amazon Q Business helps organizations use their institutional knowledge more effectively.

Wireless 105

Wireless Enterprise Chatbots APIs 105

AWS Machine Learning

SEPTEMBER 14, 2023

The following risks and limitations are associated with LLM based queries that a RAG approach with Amazon Kendra addresses: Hallucinations and traceability – LLMS are trained on large data sets and generate responses on probabilities. Please read this post to learn how to implement the RAG approach with Amazon Kendra.

APIs 124

APIs Healthcare Scripts Engineering 124