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Comprehensive IA multi-agente Tools for Every Need

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IA multi-agente

  • Multi-Agent AI on Azure with Neon & OpenAI

    A framework for deploying collaborative AI agents on Azure Functions using Neon DB and OpenAI APIs.
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    What is Multi-Agent AI on Azure with Neon & OpenAI?
    The Multi-Agent AI framework provides an end-to-end solution for orchestrating multiple autonomous agents in cloud environments. It leverages Neon’s Postgres-compatible serverless database to store conversation history and agent state, Azure Functions to run agent logic at scale, and OpenAI APIs to power natural language understanding and generation. Built-in message queues and role-based behaviors allow agents to collaborate on tasks such as research, scheduling, customer support, and data analysis. Developers can customize agent policies, memory rules, and workflows to fit diverse business requirements.
    Multi-Agent AI on Azure with Neon & OpenAI Core Features
    • Multi-Agent orchestration via Azure Functions
    • Persistent memory storage with Neon DB
    • OpenAI API integration for language models
    • Inter-agent communication and messaging
    • Scalable serverless deployment

  • Autogen Studio Research

    An experimental low-code studio for designing, orchestrating, and visualizing multi-agent AI workflows with interactive UI and customizable agent templates.
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    What is Autogen Studio Research?
    Autogen Studio Research is a GitHub-hosted research prototype for building, visualizing, and iterating on multi-agent AI applications. It offers a web-based UI that lets you drag and drop agent components, define communication channels, and configure execution pipelines. Under the hood, it uses a Python SDK to connect to various LLM backends (OpenAI, Azure, local models) and provides real-time logging, metrics, and debugging tools. The platform is designed for rapid prototyping of collaborative agent systems, decision-making workflows, and automated task orchestration.
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