AI chatbot
Use AI-powered chatbots to deliver automated conversations
Develop chatbots, AI agents, and human-like contact center experiences with Google’s industry leading AI, including Vertex AI Agent Builder.
New customers get up to $300 in free credits to try Agent Builder and other Google Cloud products.
New customers get up to $300 in free credits on signup to apply towards gen AI knowledge base solution.
Overview
What is an AI chatbot?
Artificial intelligence (AI) chatbots are apps or interfaces that can carry on human-like conversation using natural language understanding (NLU) or natural language processing (NLP) and machine learning (ML). AI chatbots differ from standard chatbots in that they leverage large language models (LLMs) versus traditional conversation flows and pre-programmed responses to generate responses to text and voice inputs.
What are the benefits of an AI chatbot?
AI chatbots can improve customer experiences with virtual agents trained on a business's content and data, lower costs, and scale customer support. AI chatbots can act as the sole point of customer contact, support human agents at call centers, recommend answers generated on the fly, and field frequent customer inquiries.
AI chatbots vs chatbots vs virtual agents
Non-AI chatbots use scripted dialog and cannot generate any responses that were not pre-programmed into the chatbot.
AI chatbots leverage AI, ML, NLU, NLP, and LLMs to deliver human-like responses to human input. AI chatbots are trained on large amounts of data and use ML to intelligently generate a wide range of non-scripted, conversational responses to human text and voice input.
Virtual agents are AI bots that can be specifically trained to interact with customers in call centers or contact centers.
What are common AI chatbot uses?
AI chatbots are commonly used as contact center solutions, real-time assistance to human agents, generative chatbots, voice capabilities, and sentiment analysis. Google Cloud's Conversational Agents (Dialogflow CX) can help you create virtual agents that use generative AI to seamlessly switch between topics and operate across multiple channels 24/7. Vertex AI Agents enables developers to build AI-powered chat apps. And Customer Engagement Suite with Google AI improves call center and customer service experiences.
RAG and chatbots
Some chatbots utilize Retrieval Augmented Generation (RAG) to overcome the limitations of their pre-programmed responses and access a wider pool of information. When a user asks a question, a RAG-powered chatbot doesn’t have to just rely on pre-written scripts. Instead, it may leverage RAG to search through external knowledge bases and documents relevant to the user's query. This could include internal wikis, product documentation, or even publicly available information on the internet.
How It Works
AI chatbots leverage LLMs (large language models) to ingest large open source or company-owned datasets—including websites, documents, and inventories. The LLM then uses this data to offer conversational responses to chat questions, improve customer experiences, and lower call center costs.
AI chatbots leverage LLMs (large language models) to ingest large open source or company-owned datasets—including websites, documents, and inventories. The LLM then uses this data to offer conversational responses to chat questions, improve customer experiences, and lower call center costs.
Common Uses
Generative AI chatbots
Build a generative AI chat app
In this codelab, you'll spin up an agent in minutes using Vertex AI Agents and Dialogflow. Connect your webpage or documents to the Dialogflow CX agent and leverage large language models for generating conversational responses from your content—out of the box and with minimal ML experience.
How-tos
Build a generative AI chat app
In this codelab, you'll spin up an agent in minutes using Vertex AI Agents and Dialogflow. Connect your webpage or documents to the Dialogflow CX agent and leverage large language models for generating conversational responses from your content—out of the box and with minimal ML experience.
Virtual agents for contact centers
Build an AI agent for contact centers
Build your own AI-powered contact center with Contact Center as a Service AI (CCaaS), an AI-driven contact center platform that is built natively on Google Cloud. CCAI works alongside CRMs and features Dialogflow for building a chatbot, Agent Assist for real-time assistance to human agents, and Conversational Insights for identifying call drivers and sentiment.
How-tos
Build an AI agent for contact centers
Build your own AI-powered contact center with Contact Center as a Service AI (CCaaS), an AI-driven contact center platform that is built natively on Google Cloud. CCAI works alongside CRMs and features Dialogflow for building a chatbot, Agent Assist for real-time assistance to human agents, and Conversational Insights for identifying call drivers and sentiment.
Conversational AI
Build a conversational AI agent
Build and train a Dialogflow CX virtual agent to answer questions, make recommendations, and handle concurrent conversations with your end users. Dialogflow CX agent's natural language module understands the nuances of human language, translating end-user text or audio during a conversation to structured data that your apps and services can understand.
How-tos
Build a conversational AI agent
Build and train a Dialogflow CX virtual agent to answer questions, make recommendations, and handle concurrent conversations with your end users. Dialogflow CX agent's natural language module understands the nuances of human language, translating end-user text or audio during a conversation to structured data that your apps and services can understand.
Generative AI knowledge base solution
Deploy a gen AI knowledge base solution to enable customer self-service
Launch a Google-recommended application that extracts question-and-answer pairs from your documents. Based on the output from the application, you can train and fine-tune a prompt-based AI model, which can be used as an example for other customer self-service use cases.
How-tos
Deploy a gen AI knowledge base solution to enable customer self-service
Launch a Google-recommended application that extracts question-and-answer pairs from your documents. Based on the output from the application, you can train and fine-tune a prompt-based AI model, which can be used as an example for other customer self-service use cases.
Start your proof of concept
New customers get up to $300 in free credits to try Vertex AI Agent Builder and other Google Cloud products
Have a large project?
Learn how to create a Dialogflow CX agent
Learn how to rapidly build and deploy pre-built virtual agents
