In our conversations with customers, few generative AI use cases have driven as much enthusiasm as generative search. Leaders at enterprises know the limits of traditional enterprise search, with queries producing a list of links based on pattern matching, and significant manual investigation required to find the more relevant answers. In generative AI, these leaders see an opportunity to leverage their data more effectively and deeply, including applying it to conversational apps that can answer complex questions, produce accurate summaries that synthesize many sources, and help people get the information they need, faster.
Enterprise Search on Generative AI App Builder (Gen App Builder) lets organizations create custom chatbots and semantic search applications in as little as a few minutes, with minimal coding needed to get started and enterprise-grade management and security built in. Customers can combine their internal data with the power of Google’s search technologies and generative foundation models, delivering relevant, personalized search experiences for enterprise applications or consumer-facing websites.
To date, most approaches to combining generative AI and search technology have been inadequate for the scale and reliability needed for enterprise use. For example, building search by breaking long documents into chunks and feeding each segment into an AI assistant typically isn’t scalable and doesn’t effectively provide insights across multiple sources. Likewise, many solutions are limited in the data types they can handle, prone to errors, and susceptible to data leakage. Bespoke, do-it-yourself approaches are generally no easier, with production-grade solutions often requiring complex tasks like integrating embeddings data with foundation models and significant use case data testing. Even when organizations make these efforts, the resulting solutions still tend to lack feature completeness and reliability, with significant investments of time and resources required to achieve high-quality results.
These challenges demonstrate that to effectively implement generative search, organizations typically need more than access to powerful foundation models. They also likely need the ability to ground model outputs in specific data, so that outputs are more relevant and less likely to include mistakes or “hallucinations.” They generally need safeguards that protect their data, how it is accessed, and how it is used. And they generally need the process to be high-performant and scalable out of the box, making the functionality easy to use even if the organization lacks data science and machine learning expertise.
Let’s look at how Enterprise Search on Gen App Builder helps customers bypass these scale and reliability challenges, so they can start leveraging generative search quickly.
The intersection of generative AI and enterprise data
Enterprise Search on Gen App Builder lets developers create search engines that help ground outputs in specific data sources for accuracy and relevance, can handle multimodal data such as images, and include controls over how answer summaries are generated. Multi-turn conversations are supported so that users can ask follow up questions as they peruse outputs, and customers have control over their data—including the ability to support HIPAA compliance for healthcare use cases. All of this is available as a fully managed service, so developers can focus on building rather than cloud complexity.
Gen App Builder’s out-of-box capabilities can remove the need for data chunking, generating embeddings, or managing indexes, hiding complexity behind a straightforward interface that lets developers build apps in minutes with little or no coding and no prior machine learning experience. With the ability to ingest large volumes of documents and support for both unstructured and structured data, apps built with Gen App Builder help customers solve the long-standing headache of finding relevant information across the organization, turning tasks that used to take hours into quick searches or conversational explorations with an app.
These capabilities are underpinned by both Google’s foundation models and a variety of Google Search technologies, including:
-
Semantic search, which helps deliver more relevant results than traditional keyword-based search techniques by using natural language processing and machine learning techniques to infer relationships within the content and intent from the user’s query input.
-
Google’s understanding of how users search for information.
-
Google’s expertise in understanding relevance, which considers factors such as content popularity and user personalization of content when determining the order in which search results are displayed.
For more advanced use cases, Gen App Builder can be easily integrated with Vertex AI for in-depth foundation model tuning, enabling flexible input and output search formats.
As always with our AI products, Gen App Builder has been evaluated for alignment with our AI Principles, which is reflected by the product’s many safeguards against bias, toxic content, and unhelpful outputs. Whether for prototypes built in minutes or apps with many custom components, Enterprise Search on Gen App Builder offers a robust suite of user-friendly tools for customers across industries and levels of expertise.
How customers are innovating with Enterprise Search
After gaining access to Enterprise Search on Gen App Builder via our trusted tester program, a number of customers are already leveraging the product for novel use cases.
Priceline is harnessing Gen App Builder and Vertex AI for a range of projects, including internal search engines for employees and a new chatbot to assist customers as they make travel plans. Slated to be available across both desktop and mobile experiences, Priceline’s chatbot will help customers find the right information faster via always-on, personalized experiences, including answering nuanced questions like, “What are the best 4-star hotel options in midtown Manhattan within walking distance to Central Park?” and “Can you help me extend my hotel reservation for an additional night?”
“Priceline is charting a course to transform the novelty of generative AI into lasting value for our customers and our business. We believe it’s not just about having the latest technology; it’s also about practically targeting innovation to the right challenges and opportunities,” said Marty Brodbeck, Chief Technology Officer, Priceline. “With Google Cloud as our AI innovation partner, we’re doubling down on our commitment to delivering the fastest, most seamless and informative booking experience for our customers, from personalized planning and travel inspiration to customer service.”
Vodafone is experimenting with Enterprise Search and foundation models on Gen App Builder to build a tool that can rapidly and securely query documents, search, and understand specific commercial terms and conditions. Vodafone Voice and Roaming Services has over 10,000 contracts with other telecommunications companies worldwide, in a variety of formats such as PDFs, images, and complex tables. Searching this document repository is often a time consuming process for employees.
“Every day we introduce and manage new services like 5G to a roaming footprint comprising more than 700 operators in 210 countries to ensure both Vodafone and our partners’ business customers, holidaymakers, and Internet of Things devices stay connected when abroad. With Enterprise Search on Gen App Builder, we are building an intelligent assistant to securely and quickly search contracts.” said Sherif Bakir, CEO of Vodafone Voice and Roaming Services. “With generative AI, we’re accelerating otherwise protracted processes, increasing productivity and operational efficiency.”
Software startup Trender.ai, which creates customer monitoring and intelligence solutions for B2B relationships, is using Gen App Builder to build a product that can synthesize information from social media, public sources, and CRM data so that users can form more productive, personal relationships with prospects and customers.
“With Enterprise Search on Gen App Builder, we have been able to do things in the last month that we had projected to take 12-18 months on our prior roadmap,” said Betsy Bilhorn, co-founder at Trender.ai. “We had expected it would take at least 12 months to build and train models from an individual’s public social, web, and other data, and to then be able to ask questions like ‘What things are most important to this person?’ or ‘When and how is the best way to make an introduction to this prospect that they’ll respond to?’ Last year, we thought getting to this vision was a bit of a moonshot for a startup our size — but now we were able to achieve this in under a month.”
Stop searching for solutions — start discovering insights
We’re excited to see how customers use Enterprise Search on Gen App Builder to leverage data in powerful ways, discover new insights, and create useful, personal, and efficient experiences.
Today, we’re pleased to help our customers accomplish these goals, with the general availability of Enterprise Search on Gen App Builder for customers on the allowlist (i.e., approved for access). Please contact your Google Cloud sales team for access and pricing details. We are also launching two new features within Enterprise Search on Gen App Builder that are available today in our preview offering: multi-turn search, which supports asking follow-up questions, and content recommendations to find semantically relevant content. Access to the preview offering is available via Google Cloud’s trusted tester program. Read more about Enterprise Search on Gen App Builder and sign up for access on our webpage.
We’re also bringing generative AI features of Enterprise Search to our existing solutions like Contact Center AI and Document AI. As an example, starting this month, customers can preview generative AI-powered search in Document AI Warehouse. To keep up with our latest generative AI news, don’t miss The Prompt or our generative AI primer for executives on Transform with Google Cloud.