Google's Vertex AI platform is a powerhouse for building cutting-edge AI solutions, and one of its standout products is Vertex AI Search and Conversation. But what’s the difference? and how do you know which one to use for your business needs? Let’s break it down.
Sample Demo links for the entire procedure: Search: Search_Demo_Full.mp4, Chat: Chat_4k_Blog_Mask.mp4
Youtube Shorts link: https://www.youtube.com/shorts/C5WnUur_N1I
Before getting into Vertex AI Search vs. Vertex AI Conversation, let’s get into Search vs. Chat. The easy way to understand the difference is this:
Search, like a librarian, gives you a list of citations that might contain the answer, possibly with the summarized response to the specific question.
Conversation, like a friend, initiates a back-and-forth chat where someone understands what you mean over time, i.e., context.
Now, think 'Search vs. Chatbot' from the perspective of Vertex AI. While they both rely on powerful Google AI technologies, Vertex AI Search and Vertex AI Conversation serve slightly different purposes.
Both products are capable of helping your ‘question’ find its ‘answer’ needle super-quickly in the enormous haystack of your documents, websites, structured data, etc. So, search and chat are possible by meaning as well, not only the ‘keywords’.
Note: Every search app has a 1:1 correspondence with a datastore, whereas a single chat app can handle multiple types of datastores.
Note: The chat app mandates advanced website indexing, which further requires domain verification. More details are here.
Verdict: Both end up with a 5:5 score. There are numerous other fine-grained and intricate distinctions as well. The detailed analysis of your use case is the primary factor that will reveal those and break the tie 🙂.
Both Vertex AI Search and Vertex AI Conversation leverage Google’s advanced foundation models for language understanding and information processing. However, they use these technologies in different ways.
Vector Search Methodology
Vertex AI Search employs vector-based search. This means it turns your text data into numerical representations, allowing it to find information based on meaning, not just exact keywords. Technically, it is based on the world’s largest and most scalable search engine (Google Search ST-MU), which combines both keyword search and semantic search.
Vertex AI Conversation combines foundation models with Dialogflow CX, Google’s powerful conversational AI platform. This gives it the ability to understand the nuances of conversation, follow the flow of a dialogue, and provide relevant responses. Thereby, it simplifies complex conversational flows and graphs via natural language prompts.
Let’s look at a few sample search and chat results related to a sample Wiki PDF ‘Tourism in India’, which are as follows:
Search Widget (Source: Vertex AI Search for Wikipedia PDF Search Widget)
Chat Widget (Source: Vertex AI Conversation for Wikipedia PDF Chatbot)
Vertex AI Search and Conversation combine to create powerful Retrieval Augmented Generation (RAG) solutions. Vertex AI Search excels at indexing and retrieving relevant information by making it discoverable from vast data sources - documents, websites, or structured data.
Meanwhile, Vertex AI Conversation acts as the generative component, crafting natural-sounding responses based on the retrieved knowledge to foster natural interactions with your customers and employees. Also, Dialogflow employs Enterprise Search to search for sources based on the user's query.
This synergy allows you to build chatbots or virtual assistants that don’t just parrot back memorized responses but instead, can access, understand, and then articulate information from your collective knowledge base.
This blog is not about the battle of two heavyweights, as Vertex AI Search and Vertex AI Conversation complement each other and don’t work in isolation. They are both powerful features for making the most of your company’s enterprise data. By using the power of this combination, the beauty of Vertex AI Search and Conversation as a whole product can be realized. By understanding their differences and potential use cases, you can choose the right tool for your specific needs.
Verdict: Neither Vertex AI Search nor Conversation individually win as a feature of Vertex AI Search and Conversation which is a single-win product and provided out-of-the-box (OOTB) as a fully-managed service.
Sample Demo links for the entire procedure: Search: Search_Demo_Full.mp4, Chat: Chat_4k_Blog_Mask.mp4
Are you ready to start your quest? Embark on your Vertex AI S&C adventure and conquer your data chaos using the reference links:
References and additional resources
Let me know in the comments if you’d like a deeper dive into any specific technology or examples of how they’re used in real-world applications! Should you have any concerns or queries about this post or my implementation, please feel free to connect with me on LinkedIn! Thanks!