Google AI Developers
@googleaidevs
Using the new Managed Agents in the Gemini API, @RampLabs built their advanced finance agents without touching the backend infrastructure. Learn more ↓ https://t.co/fmyZqGATAk
3retweets41likes
View on XRamp Deploys Finance Agents Using Google Managed Agents for Gemini API
Ramp, a finance automation platform, deployed advanced financial agents using the recently launched Managed Agents in the Gemini API. This infrastructure layer handles the underlying agent orchestration and backend hosting, allowing developers to focus on agent logic rather than server management or scaling.
This implementation validates a shift toward standardized agentic engineering. By offloading the mechanical agent loop to the model provider, companies can move from prototypes to production faster. It mirrors a broader industry trend where frontier labs provide managed environments, similar to Anthropic's Claude Managed Agents, to lower the technical barrier for enterprise-grade deployments.
You can now use Managed Agents within the Gemini API to build autonomous workflows requiring persistent state and multi-step reasoning. This approach eliminates the need for custom backend infrastructure to track agent progress or handle tool execution. The feature is currently available through the Gemini API for developers looking to scale agentic applications.
Still wondering? A few quick answers below.
Managed Agents are a specialized infrastructure layer within the Gemini API designed to handle the backend complexities of running autonomous AI agents. This service manages agent orchestration, which is the coordination of multi-step reasoning and tool use, allowing developers to deploy production-grade agents without building their own custom management systems or hosting infrastructure.
Ramp used Managed Agents to build and deploy advanced financial agents for its platform. By using this managed service, the company was able to move its agentic workflows into production without touching the underlying backend infrastructure. This allowed their engineering team to focus on the specific logic of finance tasks rather than the mechanics of agent execution.
The primary benefit is the reduction of engineering overhead required to move AI agents from prototypes to production. Managed Agents handle the persistent state and complex execution loops that autonomous agents require. This offloads the operational burden of scaling and managing agent infrastructure to Google, enabling faster deployment of sophisticated, multi-step AI applications.
Managed Agents are currently available to developers through the Gemini API. This feature is designed for teams building autonomous workflows that require more than simple chat interactions, such as those needing multi-step reasoning and tool integration. It provides a standardized way to host and execute agents directly within the Google AI developer ecosystem.
