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Build a scalable and up-to-date generative AI chatbot with Amazon Bedrock and Confluent Cloud for business loan specialists

In this post, we demonstrate how a robust and scalable generative artificial intelligence (GenAI) chatbot is built using Amazon Bedrock and Confluent Cloud. We walk through the architecture and implementation of this generative AI chatbot, and see how it uses Confluent's real-time event streaming capabilities along with Amazon's infrastructure to continually stay up to date with the latest advances from the AI landscape.

Enhancing Self-Service Efficiency in SAP SuccessFactors with Chatbots

The fascination with Artificial Intelligence (AI)-driven devices that streamline tasks continues to captivate individuals, driving the perpetual evolution of technology. Among the latest innovations captivating the tech industry’s imagination are chatbots. These virtual agents represent a culmination of advancements in artificial intelligence, marking a paradigm shift in how we interact with technology.

Our Secret to Customer-First Account Management? Using an LLM-Powered Chatbot for Sales Teams

Snowflake account managers need their fingers on the pulse of which workload shifts or performance optimizations could improve customer experience. Yet without an all-encompassing view of their customers, sales teams have to piece together customers’ wants and needs through duplicate CRM accounts and various BI tools and dashboards.

Chatbot Development Cost in 2024

In the tech-friendly era of customer service and business operations, one technological revolution has swept through like wildfire- It’s the era of ‘Mighty Chatbots’! We know that your mind must be brimming with several questions like- Before talking about the cost, let us clarify the fact about why chatbots have swiftly become an indispensable tool for every business out there and are clamoring to integrate.

MLOps Live #24: How to Build an Automated AI ChatBot

In this MLOps Live session, Gennaro, Head of Artificial Intelligence and Machine Learning at Sense, describe how he and his team built and perfected the Sense chatbot, what their ML pipeline looks like behind the scenes, and how they have overcome complex challenges such as building a complex natural language processing ( NLP) serving pipeline with custom model ensembles, tracking question-to-question context, and enabling candidate matching.

Will ChatGPT Save the Chatbot Industry? (Part II)

In part one of this two part series, I reviewed the history of the chatbot, my 2003 patent, and the reasons why the conditions weren’t right for the type of chat experience we’re all now enjoying with ChatGPT. For part two, we get into what has changed and the different ways enterprises can drive modern chatbot experiences with ChatGPT.

Deploying an LLM ChatBot Augmented with Enterprise Data

The release of ChatGPT pushed the interest in and expectations of Large Language Model based use cases to record heights. Every company is looking to experiment, qualify and eventually release LLM based services to improve their internal operations and to level up their interactions with their users and customers. At Cloudera, we have been working with our customers to help them benefit from this new wave of innovation.