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Announcing Vertex AI Agent Builder: Helping developers easily build and deploy gen AI experiences

Generative AI presents a wealth of opportunities for developers and organizations, enabling them to optimize business processes, elevate customer interactions, and discover untapped sources of revenue. To capitalize on the vast potential, builders and IT leaders need to overcome a range of challenges, including balancing the rapid experimentation and iteration of AI models, apps, and agents with costs, governance, and performance at scale.

To help our customers manage these obstacles and accelerate the development of gen AI agents, we’re pleased to announce Vertex AI Agent Builder, which brings together our Vertex AI Search and Conversation products, along with a number of enhanced tools for developers.  

Google Cloud customers already working with these offerings are building exciting use cases. 

On the customer experience front, ADT is building an agent to help its over 6 million customers select and set up their home security systems; Intercontinental Hotels Group will launch a generative AI-powered travel planning capability that will help guests easily plan their next vacation; and NewsCorp is using Vertex AI to help search data across 30,000 global sources and 2.5 billion news articles updated daily. 

Meanwhile, other Google Cloud customers are building agents to boost internal efficiency. For example, researchers at Mayo Clinic are leveraging Vertex AI Agent Builder to search over 50 petabytes of clinical data. Vodafone has also developed a tool using Vertex AI to rapidly and securely query documents and understand specific commercial terms and conditions across over 10,000 contracts. We’re thrilled to see this momentum and look forward to continued customer innovation in the months to come.  

Let’s take a closer look at Vertex AI Agent Builder’s capabilities. 

Fast and powerful for experts, simple and accessible for novices

Vertex AI Agent Builder lets developers easily build and deploy enterprise-ready gen AI experiences via a range of tools for different developer needs and levels of expertise — from a no-code console for building AI agents using natural language, to open-source frameworks like LlangChain on Vertex AI.

Additionally, Vertex AI Agent Builder streamlines the process of grounding generative AI outputs in enterprise data. It offers not only Vertex AI Search as an out-of-the-box grounding system, but also RAG (or retrieval augmented generation) APIs for document layout processing, ranking, retrieval, and performing checks on grounding outputs. Developers can also use vector search to build embeddings-based agents and applications, increasing the accuracy and usefulness of model responses. Security and enterprise controls are built-in, making Vertex AI Agent Builder a one-stop solution for quickly creating and deploying production-ready gen AI-powered experiences. 

Building enterprise-grade, factually grounded AI agents — fast  

Whereas gen AI models offer incredible content creation and analysis capabilities, AI apps have to package those capabilities in a secure, useful interface. AI agents need to go even further, combining model capabilities with external systems so the agent can offer deep personalization and execute actions on the user’s behalf. Vertex AI Agent Builder helps to streamline these processes.

Easily build production-grade AI agents using natural language
The no-code agent building console in Vertex AI Agent Builder enables developers to build and deploy generative AI agents using Google’s latest Gemini models. To start building agents, developers navigate to the Agents section in Vertex AI. Here, they can create new agents in minutes. All they need to do is define the goal they want the agent to achieve, provide step-by-step instructions that the agent should follow to achieve that goal, and share a few conversational examples for the agent to follow. 

For complex goals, developers can easily stitch together multiple agents, with one agent functioning as the main agent and others as subagents. A subagent can pass information to another subagent or the main agent, allowing for seamless and sophisticated workflows. These agents can easily call functions, connect to enterprise data to improve response factuality, or connect to applications to perform tasks for the user. 

The Vertex AI agents console also features advanced tooling to make agent building, orchestration, and maintenance easier, including the ability to create production-grade, high-quality agents out of a prototype, monitor the performance of agents in real-time, and improve responses for specific queries by training them using natural language.

Easily build production grade AI agents using natural language in Vertex AI’s no code agents console

Grounded outputs and capable agents
Gen AI models are familiar only with the information that they were trained on. Most enterprise use cases require supplementing the model’s training knowledge with other data sources to ground outputs in relevant, factual information. Commonly referred to as Retrieval Augmented Generation, or RAG, this technique can be complicated to implement, with few specialized tools available for evaluating and maintaining the quality of grounding mechanisms over time. 

Vertex AI Agent Builder offers comprehensive capabilities to ground model outputs in enterprise data, including Vertex AI Search’s out-of-box RAG system. Only a few clicks are necessary to get up and running, and with pre-built components, the platform makes it simple to create, maintain, and manage more complicated implementations. Thanks to a variety of RAG APIs for tasks like document layout, ranking, and retrieval, developers can quickly and easily perform checks on grounding outputs. For more complex implementations, Vertex AI Agent Builder also offers powerful vector search to build custom embeddings-based RAG systems. Vector search can scale to billions of vectors, find the nearest neighbors in a few milliseconds, and combine with keyword-based search techniques to ensure the most relevant and accurate responses for users.

Customers also have the option of grounding model outputs in Google Search, combining the power of Google’s latest foundation models with access to fresh, high-quality information that can significantly improve completeness and accuracy of responses. Google is the only cloud provider to offer customers out-of-the-box grounding capabilities on both their own data and Google Search results. 

Additionally, Vertex AI Agent Builder makes it easy to augment grounding outputs and take action on your user’s behalf with extensions, function calling, and data connectors. 

Vertex AI extensions are pre-built reusable modules to connect a foundation model to a specific API or tool. For example, our new code interpreter extension enables models to execute tasks that entail running Python code, such as data analysis, data visualization, and mathematical operations. 

Vertex AI function calling enables a user to describe a set of functions or APIs and have Gemini models intelligently select, for a given query, the right API or function to call, along with the appropriate API parameters.

Vertex AI data connectors help ingest data from enterprise and third-party applications like ServiceNow, Hadoop, and Salesforce, connecting generative applications to commonly-used enterprise systems.

Enterprise-grade security and reliability
Moving from a working prototype to a production-ready app or agent can be fraught with technical challenges. Vertex AI Agent Builder eases these concerns with support for a range of compliance and security standards, including HIPAA, ISO 27000-series, and SOC-1/2/3, VPC-SC and CMEK. It also integrates with Vertex AI Studio, which lets developers leverage model tuning capabilities and easily connect with Vertex AI’s other out-of-the-box offerings for unified workflows. All capabilities come with standard access controls, data governance tools, and data sovereignty options that Google Cloud customers have come to expect, ensuring builders can focus on innovating while keeping data safe and services reliable. 

Enter the era of AI agents today

Try Vertex AI Agent Builder’s no-code agent building console to build your AI agents using natural language prompts or our open-source offerings like LangChain on Vertex AI.

To learn more about Vertex AI Agent Builder visit our webpage.

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