Scint is a powerful no-code AI Agent platform enabling users to compose, deploy, and manage autonomous multi-step workflows. With Scint’s drag-and-drop interface, users define agent behaviors, connect APIs and data sources, and set triggers. The platform offers built-in debugging, version control, and real-time monitoring dashboards. Designed for both technical and non-technical teams, Scint accelerates automation development, ensuring reliable execution of complex tasks from data processing to customer support handling.

The Multi-Agent-based Search and Rescue System in ROS is a robotics framework that leverages ROS for deploying multiple autonomous agents to perform coordinated search and rescue operations. Each agent uses onboard sensors and ROS topics for real-time mapping, obstacle avoidance, and target detection. A central coordinator assigns tasks dynamically based on agent status and environment feedback. The system can be run in Gazebo or on actual robots, enabling researchers and developers to test and refine multi-robot cooperation, communication protocols, and adaptive mission planning under realistic conditions.

Operit is a comprehensive open-source AI agent framework designed to streamline the creation of autonomous agents for various tasks. By integrating with LLMs like OpenAI’s GPT and local models, it enables dynamic reasoning across multi-step workflows. Users can define custom plugins to handle data fetching, web scraping, database queries, or code execution, while Operit manages session context, memory, and tool invocation. The framework offers a clear API for building, testing, and deploying agents with persistent state, configurable pipelines, and error-handling mechanisms. Whether you’re developing customer support bots, research assistants, or business automation agents, Operit’s extensible architecture and robust tooling ensure rapid prototyping and scalable deployments.

CopilotKit is an open-source Python framework designed for developers to build customized AI agents. It offers a modular architecture where you can register and configure tools — such as file system access, web search, Python REPL, and SQL connectors — then wire them into agents that leverage any supported LLM. Built-in memory modules allow conversation state persistence, while LangGraph lets you define structured reasoning flows for complex tasks. Agents can be deployed in scripts, web services, or CLI apps and scale across cloud providers. CopilotKit works seamlessly with OpenAI, Azure OpenAI, and Anthropic models, empowering automated workflows, chatbots, and data analysis bots.

Nova provides a comprehensive toolkit for creating autonomous AI agents in Python. It offers a planner that decomposes goals into actionable steps, a plugin system to integrate any external tools or APIs, and a memory module to store and recall conversation context. Developers can configure custom behaviors, track agent decisions through logs, and extend functionality with minimal code. Nova streamlines the entire agent lifecycle from design to deployment.

Overeasy is a Python-based open-source framework for orchestrating LLM-driven AI agents across various domains. It provides a modular architecture to define agents, configure memory stores, and integrate external tools such as APIs, knowledge bases, and databases. Developers can connect to OpenAI, Azure, or self-hosted LLM endpoints and design dynamic workflows involving single or multiple agents. Overeasy’s orchestration engine handles task delegation, decision making, and fallback strategies, enabling robust digital workers for research, customer support, data analysis, scheduling, and more. Comprehensive documentation and example projects accelerate deployment on Linux, macOS, and Windows.