ai chatbot
ai chatbot
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What is This About?
Building an AI chatbot has never been easier with Google tools. In this case, we will be looking at how we can build one for the most basic use case within 30 minutes! This loosely follows the concept of Retrieval Augmented Generation (RAG), where an Generative AI model based AI chatbot can have an open ended "discussion" about a topic, based on grounded data from stored references such as PDF doc, websites, database, etc.
This can serve many purposes such as:
Rules, policies and action plan related communications
Project / process related information
Product related information.
Basically anything - as long it has a data / information that needs to be communicated on demand in a casual manner.
Who Can Benefit From This?
HR department to communicate the details about company policies, leave policies, etc.
Project team to provide all basic and key information related to the project, implementation, team members, etc.
ESG team to communicate with both internal and external stakeholder regarding companies ESG policies, vendor requirement, environmental performance data, etc.
Software use guide, product details, etc.
Tools Used:
Google Cloud: Conversational Agents platform to configure the AI chatbot using "no-code" method.
Google Cloud: Storage Bucket to store the reference data
Google Cloud Services: Vertex AI API & Dialogflow API.
Implementation Steps - Conceptual
How to guide:
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