AWS Machine Learning

JULY 2, 2024

In November 2023, we announced Knowledge Bases for Amazon Bedrock as generally available. Knowledge bases allow Amazon Bedrock users to unlock the full potential of Retrieval Augmented Generation (RAG) by seamlessly integrating their company data into the language model’s generation process.

Healthcare 135

Healthcare APIs Government Accountability 135

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

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 123

APIs Engineering Chatbots Management 123

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 136

APIs Enterprise Best practices Accountability 136

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 133

Chatbots Banking APIs Enterprise 133

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 135

Chatbots Engineering APIs Technology 135

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 108

APIs Chatbots Construction Engineering 108

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 127

Chatbots Entertainment APIs Advertising 127

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 121

APIs Chatbots Engineering Accountability 121

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

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

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 95

Chatbots APIs Scripts Management 95

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 129

Engineering Chatbots APIs Benchmark 129

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 124

Chatbots Engineering Enterprise Feedback 124

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 107

Sales Accountability APIs CRM 107

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

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 135

Self service APIs Transportation Contact Center 135

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

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 4, 2024

Chatbot deployments : Power customer service chatbots that can handle thousands of concurrent real-time conversations with consistently low latency, delivering the quality of a larger model but at significantly lower operational costs. If you haven’t done this yet, see to the prerequisites section for instructions.

APIs 126

APIs Metrics Healthcare Chatbots 126

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 83

Sales Advertising Engineering APIs 83

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 127

Chatbots Feedback Engineering Entertainment 127

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 106

Wireless Enterprise APIs Chatbots 106

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 130

APIs Healthcare Scripts Engineering 130

AWS Machine Learning

OCTOBER 2, 2024

Whether you are developing a customer service chatbot or a virtual assistant, there are numerous considerations to keep in mind, from defining the agent’s scope and capabilities to architecting a robust and scalable infrastructure. Knowledge Base: bankingFAQ Should I invest in bitcoins? We do not provide investment advices.

Best practices 103

Best practices APIs Metrics Accountability 103

AWS Machine Learning

NOVEMBER 1, 2024

Although tagging is supported on a variety of Amazon Bedrock resources —including provisioned models, custom models, agents and agent aliases, model evaluations, prompts, prompt flows, knowledge bases, batch inference jobs, custom model jobs, and model duplication jobs—there was previously no capability for tagging on-demand foundation models.

APIs 141

APIs Management Accountability Metrics 141

AWS Machine Learning

DECEMBER 6, 2023

To create AI assistants that are capable of having discussions grounded in specialized enterprise knowledge, we need to connect these powerful but generic LLMs to internal knowledge bases of documents. To understand these limitations, let’s consider again the example of deciding where to invest based on financial reports.

Analytics 133

Analytics APIs Engineering Construction 133

AWS Machine Learning

APRIL 8, 2024

RAG allows models to tap into vast knowledge bases and deliver human-like dialogue for applications like chatbots and enterprise search assistants. It provides tools that offer data connectors to ingest your existing data with various sources and formats (PDFs, docs, APIs, SQL, and more). Query the knowledge base.

APIs 130

APIs Engineering Accountability Construction 130

AWS Machine Learning

SEPTEMBER 13, 2024

The application generates SQL queries based on the user’s input, runs them against an Athena database containing CUR data, and presents the results in a user-friendly format. The LangChain code uses the BedrockChat class from LangChain to invoke the FM and interact with Amazon Bedrock to generate a SQL query based on the user’s input.

APIs 97

APIs Chatbots Best practices Management 97

AWS Machine Learning

JUNE 12, 2024

Solution overview In this solution, we deploy a custom web experience for Amazon Q to deliver quick, accurate, and relevant answers to your business questions on top of an enterprise knowledge base. The workflow includes the following steps: The user accesses the chatbot application, which is hosted behind an Application Load Balancer.

APIs 138

APIs Enterprise Accountability Feedback 138

AWS Machine Learning

DECEMBER 22, 2023

Amazon Bedrock is a fully managed service that makes leading FMs from AI companies available through an API along with developer tooling to help build and scale generative AI applications. The web channel includes an Amplify hosted website with an Amazon Lex embedded chatbot for a fictitious customer.

Scripts 132

Scripts Chatbots Accountability Multi-channel support 132

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 96

Chatbots Metrics Scripts APIs 96

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 127

APIs Engineering Chatbots Construction 127

AWS Machine Learning

JUNE 25, 2024

Figure: 4 In the CloudWatch console you have the option to create custom dashboards Under Custom Dashboards , you should see a dashboard called Contextual-Chatbot-Dashboard. The number of the indexing and search operations on the OpenSearch Serverless collection that was created when you created your knowledge base.

Metrics 129

Metrics APIs Government Big data 129

AWS Machine Learning

NOVEMBER 27, 2024

The following diagram illustrates the end-to-end architecture, consisting of the metadata API layer, ingestion pipeline, embedding generation workflow, and frontend UI. The RDF is converted into text and loaded into an S3 bucket, which is accessed by Amazon Bedrock (4) as the source of the knowledge base.

Enterprise 114

Enterprise APIs Accountability Engineering 114

AWS Machine Learning

AUGUST 15, 2023

By taking advantage of embedding models of LLMs, and powerful indexers and retrievers, RAG can comprehend and process spoken or written queries and quickly find the most relevant information in the knowledge base. It’s important for most RAG solutions to run on the knowledge base with the same language.

Chatbots 94

Chatbots Enterprise Accountability Best practices 94