Agent Starter Pack is a developer toolkit that scaffolds intelligent, interactive agents on Google Cloud. It offers templates in Node.js and Python to manage conversation flows, maintain long-term memory, and perform tool and API invocations. Built on Vertex AI and Cloud Functions or Cloud Run, it supports multi-step planning, dynamic routing, observability, and logging. Developers can extend connectors to custom services, build domain-specific assistants, and deploy scalable agents in minutes.

Firebase GenKit is a developer framework that streamlines the creation of generative AI features using Firebase services. It includes Cloud Functions templates for invoking LLMs, Firestore triggers to log and manage prompts/responses, authentication integration, and front-end UI components for chat and content generation. Designed for serverless scalability, GenKit lets you plug in your choice of LLM provider (e.g., OpenAI) and Firebase project settings, enabling end-to-end AI workflows without heavy infrastructure management.

Inngest is a powerful AI platform designed for developers to construct web applications through serverless functions. It offers a no-code interface, enabling seamless integration of various APIs and services. With Inngest, users can automate workflows and manage event-driven mechanics efficiently, minimizing the need for extensive coding and maximizing productivity. This platform streamlines backend processes while ensuring that applications remain scalable and easy to maintain.

Rowy is an open-source, low-code platform designed to simplify backend development tasks. It utilizes a spreadsheet-like UI to manage Firestore data and facilitates the effortless writing of Cloud Functions directly in the browser. It aims to accelerate development processes, allowing for scalable backend solutions without the need for extensive coding. Integrated with Google Cloud and Firebase, Rowy is ideal for quickly building prototypes that can scale efficiently, enabling developers to focus more on creativity and less on operational complexities.

Serverless AI Agent simplifies the creation and deployment of autonomous AI agents by leveraging serverless cloud functions. By defining agent behaviors in simple configuration files, developers can enable AI-driven workflows that process natural language input, interact with APIs, execute database queries, and emit events. The framework abstracts infrastructure concerns, automatically scaling agent functions in response to demand. With built-in state persistence, logging, and error handling, Serverless AI Agent supports reliable long-running tasks, scheduled jobs, and event-driven automations. Developers can integrate custom middleware, choose from multiple cloud providers, and extend the agent’s capabilities with plugins for monitoring, authentication, and data storage. This results in rapid prototyping and deployment of robust AI-powered solutions.