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  • Open-source framework orchestrating autonomous AI agents to decompose goals into tasks, execute actions, and refine outcomes dynamically.
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    What is SCOUT-2?
    SCOUT-2 provides a modular architecture for building autonomous agents powered by large language models. It includes goal decomposition, task planning, an execution engine, and a feedback-driven reflection module. Developers define a top-level objective, and SCOUT-2 automatically generates a task tree, dispatches worker agents for execution, monitors progress, and refines tasks based on outcomes. It integrates with OpenAI APIs and can be extended with custom prompts and templates to support a wide range of workflows.
    SCOUT-2 Core Features
    • Hierarchical goal decomposition
    • Automated task planning
    • LLM-powered task execution
    • Task tracking and status monitoring
    • Iterative reflection and refinement
    • Customizable agent templates
  • A web-based AI agent platform enabling autonomous task planning and execution with API tool integration.
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    What is Agentic AI?
    Agentic AI provides a fully web-based environment where users define objectives for autonomous agents. Each agent analyzes goals, selects appropriate tools or APIs, executes tasks in sequence, and adapts based on intermediate results. The platform includes memory management for context retention, a monitoring dashboard for real-time progress, and customizable agent configurations. Agents can interact with external services, fetch data, generate reports, and perform automated decision-making to streamline operational workloads.
  • Orchestrates multiple AI agents in Python to collaboratively solve tasks with role-based coordination and memory management.
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    What is Swarms SDK?
    Swarms SDK simplifies creation, configuration, and execution of collaborative multi-agent systems using large language models. Developers define agents with distinct roles—researcher, synthesizer, critic—and group them into swarms that exchange messages via a shared bus. The SDK handles scheduling, context persistence, and memory storage, enabling iterative problem solving. With native support for OpenAI, Anthropic, and other LLM providers, it offers flexible integrations. Utilities for logging, result aggregation, and performance evaluation help teams prototype and deploy AI-driven workflows for brainstorming, content generation, summarization, and decision support.
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