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In the past year, enterprises saw an explosion of platforms where they can build AI agents, preferably with as little code as possible. With the growth of agentic ecosystems from organizations, it’s not a surprise that large model providers are starting to develop all-in-one platforms for creating agents and managing these.
For this reason, Google announced today that it has expanded its agentic offerings, competing against many other agent-building platforms. However, Google said its new Agent Development Kit (ADK) and other additional capabilities also offer control over how agents behave.
The company said the ADK simplifies the creation of multi-agent systems on Gemini models. Google claims users can “build an AI agent in under 100 lines of intuitive code” with ADK. The platform also supports the Model Context Protocol (MCP), the data connection protocol developed by Anthropic that helps standardize data movement between agents.
Google said ADK will help organizations:
Shape how agents think, reason, and collaborate with orchestration controls and guardrails
Interact with agents “in human-like conversations with ADK’s unique bidirectional audio and video streaming capabilities”
Jumpstart development with a collection of ready-to-use sample agents and tools
Choose the best model for the agent from Google’s Model Garden
Select the deployment target, whether it’s Kubernetes or Google’s Vertex AI
Deploy agents directly to production through Vertex AI
ADK is optimized for Gemini models, though Vertex AI allows access to models from Anthropic, Meta, Mistral, AI21 Labs, CAMB.AI and Qodo. Google said developers can use ADK to ground agent and application responses to different data connectors.
More agentic support
Google also introduced Agent Engine, a managed runtime dashboard parallel to ADK with enterprise-grade controls.
Google told reporters in a briefing that Agent Engine allows organizations to go from concept to training to eventual production. It handles “agent context, infrastructure management, scaling complexities, security, evaluation and monitoring.”
Agent Engine integrates with ADK but can be deployed on other frameworks like LangGraph or CrewAI.
With short—and long-term memory support, users can keep context for agents. They can customize how much or how little information from past conversations or sessions the agents can pull.
Agent Engine also lets enterprises evaluate the agents’ behavior and reliance during real-time usage.
Companies wanting more help building agents can access Google’s new Agent Garden. Agent Garden, like a model garden, is a library of pre-built agents and tools that users can use to model their agents.
Managing agents
A big concern for many organizations around agents is security and trust. There are many new approaches to improve the reliability and accuracy of agents.
Google’s version, through ADK and Vertex AI, would bring additional configurations for enterprises. These include:
Controlling agent output with content filters and defined boundaries, and prohibited topics
Identity controls with agent permissions
Secure parameters on which data agents can access to limit sensitive data leaks
Guardrails, including screening inputs before they reach the models that run agents
Auto-monitoring agent behavior
Agent platform competition heats up
Enterprises have previously been able to build agents with Google’s AI services. Still, the launch of ADK and its other agentic AI offerings puts Google more in competition with other agent providers. Technology companies are increasingly offering an all-in-one agent-building platform.
Google has to prove that its one-stop agent creation platform, optimized for Gemini models and Vertex AI, is a better choice.
OpenAI released Agents SDK in March, which lets people build agents with open-source tools, including non-OpenAI models. Agents SDK also offers configurable enterprise security and guardrails. Amazon’s Agents on Bedrock, launched in 2023, also allows organizations to build agents in one place and Bedrock was updated to provide orchestration capabilities last year.
Newcomer Emergence AI released an agent builder platform that lets people make any AI agent they need on the fly. Human users specify the task they need to finish, and AI models create the agents to accomplish it.
