Systems | Development | Analytics | API | Testing

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.

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.

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.

LLM ChatBot Augmented with Enterprise Data

This video demonstrates how to use an open source pre-trained instruction-following LLM (Large Language Model) to build a ChatBot-like web application. The responses of the LLM are enhanced by giving it context from an internal knowledge base. This context is retrieved by using an open source Vector Database to do semantic search.