What I like best about Vertex AI Search is how quickly it enables the creation of intelligent, AI-powered search experiences with minimal setup. It delivers highly relevant search results using Google's advanced language models, understands natural language queries, and provides accurate, context-aware responses. The seamless integration with other Google Cloud services, scalability, and enterprise-grade security make it a great choice for building internal knowledge bases, customer support portals, and document search applications. Review collected by and hosted on G2.com.

One drawback of Vertex AI Search is that the initial setup and configuration can feel complex, especially for teams that are new to the Google Cloud ecosystem. Fine-tuning search relevance and managing indexing may require some experimentation, and the pricing can become expensive as data volume and query traffic grow. While the documentation is comprehensive, some advanced features have a learning curve and could benefit from more practical examples and easier configuration. Review collected by and hosted on G2.com.

What I like most about Vertex AI Search is how it combines semantic search with generative AI to deliver accurate, context-aware results. It integrates smoothly with the Google Cloud ecosystem, supports retrieval-augmented generation (RAG) out of the box, scales well for enterprise use cases, and requires very little infrastructure management. The strong search relevance, natural language understanding, and grounded AI responses make it especially well suited for knowledge bases, documentation search, and conversational AI applications. Review collected by and hosted on G2.com.

The biggest drawbacks are the pricing, which can get expensive as usage and indexed data grow, and the learning curve involved in configuring relevance tuning and other advanced search features. The initial setup and integration can also feel complex, especially for teams that are new to Google Cloud. I’d also like to see more transparent debugging tools for understanding search rankings, additional data connectors, and more granular control over retrieval and ranking behavior. Review collected by and hosted on G2.com.

The information which we are looking for - that can be obtained using a natural language query and looking for general information is quite reliable, which you would get using google search. Review collected by and hosted on G2.com.

Grounding is a disaster, grounding metadata is pretty useless and most of the links given by vertex ai search lead to dead links, so it's not useful for looking up real time information especially like ecommerce data. Review collected by and hosted on G2.com.

What stands out about vertex ai search is that its fully managed RAG capability Review collected by and hosted on G2.com.

What I dislike about Vertex AI Search is that it gets expensive very quickly when you use it a lot. Setting it up is hard if you aren't already using Google Cloud Review collected by and hosted on G2.com.

Honestly, Vertex AI Search just makes life so much easier. It takes all the headache out of building generative AI search apps and gives teams a ready-to-use platform that gets up and running incredibly fast.

Here’s what stands out most to me from a TAM perspective:

No more duct-taping tools together: Building AI search usually means piecing together vector databases, embedding models, and custom code. Vertex does all that heavy lifting for you right out of the box. Teams can go from a cool idea to a working app in days instead of months.

It actually cites its sources: This is a massive win for clients. The AI grounds its answers strictly in your own data and provides exact citations and links back to the original documents. It really cuts down on the AI "hallucinating" or making things up, which builds so much trust with users. Review collected by and hosted on G2.com.

As much as I love the platform, it’s not a magic wand. If your team isn't already comfortable navigating Google Cloud, the setup can feel a bit overwhelming, and if you aren't careful, the costs can sneak up on you. Review collected by and hosted on G2.com.

Although I couldn't get my head around using it and setting it up, I do like the principle. I like how you can create your own data base, upload all your documents, websites, spreadsheets etc and put them into your own database for searching or using an ai to read and to chat with about certain information Review collected by and hosted on G2.com.

I just couldn't get my head around using it. although it seems easy to set up, I just couldn't do it. no amount of videos or guides was helping me set it up. it was too complicated for me to understand and the user interface felt a bit messy Review collected by and hosted on G2.com.

Vertex AI Search is fast and easy to use. It helps me find the right information quickly, so I don’t have to spend much time searching. Review collected by and hosted on G2.com.

I’d really like to see a simpler setup process and more affordable pricing options for smaller teams. A few of the features also come with a bit of a learning curve, so it can take some time to get fully comfortable with everything. Review collected by and hosted on G2.com.

It makes Compliance Online's information feel instantly accessible without employees needing to know exactly where each document is stored or which word to search for. Review collected by and hosted on G2.com.

There is quite a lot of effort in the initial setup stage. If you have multiple versions of the same document or instructions that differ due to updates/changes it results in inconsistent answers. Review collected by and hosted on G2.com.

We’ve been using Vertex AI for our RAG pipeline built around Cloud Storage files and BigQuery data. So far, it’s been working great with the new Gemini version. Semantic search is also working well. Review collected by and hosted on G2.com.

It doesn’t support complete, exact data and, in most cases, only covers partial data. Review collected by and hosted on G2.com.

It leverages google’s search expertise and provides a grounded reply with minimal implementation effort Review collected by and hosted on G2.com.

Its a a huge ecosystem dependencies. Also, the search quality is dependent on content quality. Cost is also an aspect to be unhappy Review collected by and hosted on G2.com.