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gestão de memória contextual

  • AI Foundry is a no-code platform to build autonomous AI agents by chaining LLMs, APIs, memory and triggers into workflows.
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    What is AI Foundry?
    AI Foundry offers a comprehensive no-code environment to construct custom AI agents that autonomously perform complex tasks. Users create workflows using a visual builder, chaining language models, REST APIs, database connectors and memory stores. Each agent can be configured with event triggers, scheduling options, execution logs and collaboration features. Test agents interactively before deploying them as API endpoints or embedding them into applications. Built-in monitoring and analytics provide real-time insights into performance and usage. AI Foundry scales horizontally, supports role-based access controls for teams, and ensures secure data handling, enabling businesses and developers to automate processes such as customer support automation, research assistance, report generation or lead qualification quickly and reliably.
    AI Foundry Core Features
    • Visual no-code workflow builder
    • Multi-LLM orchestration
    • API and data connector integrations
    • Memory and context management
    • Event triggers and scheduling
    • Real-time logging and monitoring
    • Team collaboration and access control
    • One-click deployment as API endpoints
    AI Foundry Pro & Cons

    The Cons

    The Pros

    Provides hands-on tutorials for AI development
    Includes production-ready code samples
    Focuses on best practices and development patterns for Azure AI
  • BlueMarz.ai empowers businesses to build, deploy, and manage custom AI agents for complex automated workflows.
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    What is BlueMarz.ai?
    BlueMarz.ai provides a comprehensive environment to design, build, and operate intelligent AI agents for a variety of business use cases. Users can choose from an extensive library of templates or define custom conversation flows using a visual builder. The platform’s memory management feature stores and retrieves context throughout interactions, enabling agents to deliver personalized responses. Integration with APIs, databases, and third-party services ensures seamless data access, while built-in connectors allow deployment on web channels, Slack, and Microsoft Teams. Administrators can monitor agent performance through real-time dashboards, manage version control, and set security permissions. Overall, BlueMarz.ai reduces development complexity, accelerates time-to-market, and scales agent deployments to meet evolving operational demands.
  • A Python framework to build and orchestrate autonomous AI agents with custom tools, memory, and multi-agent coordination.
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    What is Autonomys Agents?
    Autonomys Agents empowers developers to create autonomous AI agents capable of executing complex tasks without manual intervention. Built on Python, the framework provides tools for defining agent behaviors, integrating external APIs and custom functions, and maintaining conversational memory across interactions. Agents can collaborate in multi-agent setups, sharing knowledge and coordinating actions. Observability modules offer real-time logging, performance tracking, and debugging insights. With its modular architecture, teams can extend core components, incorporate new LLMs, and deploy agents across environments. Whether automating customer support, performing data analysis, or orchestrating research workflows, Autonomys Agents streamlines end-to-end development and management of intelligent autonomous systems.
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