TLDR: Vertex AI provides a platform for building and managing multi-agent AI systems. It offers the Agent Development Kit (ADK) for creating agents, the Agent2Agent (A2A) protocol for agent collaboration, and Agent Engine for deployment and management. It also emphasizes security and offers use cases for SMBs, such as customer support and sales assistance.
Every enterprise will soon rely on multi-agent systems – multiple AI agents working together to accomplish tasks across various systems. These intelligent systems, capable of reasoning, planning, and remembering, can act on your behalf under your supervision, thinking multiple steps ahead. Google Cloud’s Vertex AI offers a comprehensive platform to build and manage these sophisticated systems by seamlessly orchestrating models, data, and agents. This article provides a developer-focused guide on leveraging Vertex AI to create and deploy robust multi-agent solutions.
Agent Development Kit (ADK)
ADK is an open-source framework within Vertex AI that streamlines the development of individual and multi-agent systems. ADK shares the same foundational technology as Google Agentspace and Google Customer Engagement Suite (CES) agents, and empowers developers to precisely control agent behavior. With ADK’s intuitive code structure, building an AI agent can be achieved in under 100 lines of code.
Key Features of the Agent Development Kit (ADK)
- Provides developers with deterministic guardrails and orchestration controls to precisely shape agent behavior.
- Enables human-like interaction through unique bidirectional audio and video streaming capabilities.
- Accelerates development by offering pre-built agent samples and tools through Agent Garden.
- Supports flexible model selection, compatible with a wide range of models including Gemini, Model Garden, and over 200 models from external providers.
Agent2Agent
Agent2Agent (A2A) protocol by Google Cloud addresses the challenge of seamless collaboration between agents built on different frameworks. With over 50 industry leaders involved, A2A enables secure communication and interaction between agents across diverse ecosystems, regardless of their underlying technology.
Accessing Enterprise Data with Vertex AI
- Vertex AI provides multiple ways for agents to access enterprise data.
- The Model Context Protocol (MCP) enables connections to MCP-compatible tools and data sources.
- Direct connections are possible using pre-built connectors, workflows, or data stored in systems like AlloyDB and BigQuery.
- ADK supports integration with existing agents and tools and can call tools from various sources.
Agent Engine
Agent Engine in Vertex AI simplifies the deployment and management of AI agents by providing a fully managed runtime that handles crucial aspects like context, infrastructure, scaling, and security. This allows developers to focus on building innovative solutions instead of managing infrastructure.
Key Benefits of Agent Engine
- Framework-Agnostic Deployment: Deploy agents built with various frameworks and models.
- Persistent Context: Maintain short-term and long-term session context for agents.
- Quality Measurement and Improvement: Utilize Vertex AI tools to evaluate and enhance agent performance.
- Broader Adoption through Agentspace: Register agents on Agent Engine for accessibility within a secure environment.
Enterprise-Grade Security
To safely run AI agents in production, strong security measures are essential to counter threats like prompt injection and unauthorized data access. Vertex AI offers multiple layers of security, enabling your enterprise to construct trustworthy agents.
Enterprise-Grade Security for Trusted AI Agents
- Controlled agent output through configurable content filters and system instructions.
- Managed agent permissions using identity controls to prevent privilege escalation.
- Protected sensitive data by confining agent activity within secure perimeters.
- Established guardrails by screening inputs and validating parameters before tool execution.
- Auto-monitored agent behavior through comprehensive tracing capabilities.
Use case For SMBs
- Customer Support: Instant responses to common inquiries, freeing human agents for complex issues.
- Sales Assistance: Guiding customers, answering questions, and assisting with orders.
- Data Access and Analysis: Quick access to insights and automation of basic data analysis.
- Internal Workflow Automation: Automation of repetitive internal processes, like scheduling and document processing
Consider a small online retailer as an example of an SMB that could utilize ADK to create an AI agent capable of addressing common customer inquiries regarding shipping times, return policies, and product availability. This agent could be incorporated into the website’s chat feature and use pre-built connectors to retrieve information from their order management system or knowledge base. The Agent Engine would then manage the deployment and maintenance of this customer service agent, providing round-the-clock support, enhancing customer satisfaction, and decreasing the workload of the retailer’s customer service team.
Vertex AI provides a comprehensive platform for building and managing multi-agent systems. It empowers developers to create scalable AI solutions through the Agent Development Kit, Agent2Agent protocol, and Agent Engine, while prioritizing open standards, robust features, and enterprise-grade security. .
