Build an AI Chatbot that integrates email support


Summary

The video introduces a new conversational pipeline at Vector Shift, detailing options available to users and three types of mappings between inputs and outputs. It explains automating processes like sales proposals using triggers and pipelines, covering start flags, messages, and buttons within the chatbot interface. The process of requesting a demo is guided, including the use of branches for defining steps and entering booking URL. Additionally, it covers contacting customer support, capturing support inquiries, and responding within specific timeframes. A chat assistant is created to provide information from a knowledge base, utilizing a scrape URL, capturing responses, querying data, and presenting context-based responses using a large language model.


Introduction to Conversational Pipeline

Introducing a new conversational pipeline at Vector Shift, explaining the options presented to users at the beginning of a chatbot interaction, and discussing the three different types of mappings between inputs and outputs in Vector Shift.

Building Automations with Triggers and Pipelines

Explaining how to automate processes like sales proposals with triggers and pipelines in Vector Shift, covering the start flag on the map and the typical messages and buttons users encounter in the chatbot.

Handling Book a Demo Option

Guiding users through the process of requesting a demo, explaining the use of branches to define steps, entering the URL for booking a demo, and handling the path for booking a demo through emails.

Contacting Customer Support

Detailing the process of contacting customer support through email inquiries, capturing user emails and support ticket inquiries, sending confirmation emails, and responding to user inquiries within specific timeframes.

Creating a Chat Assistant

Creating a chat assistant to provide information from a knowledge base using a scrape URL, capturing responses, querying data, using a large language model, and presenting responses based on the captured context.

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