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  • Jaaz is a Node.js-based AI agent framework enabling developers to build customizable conversational bots with memory and tool integrations.
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    What is Jaaz?
    Jaaz is an extensible AI agent framework designed for crafting highly interactive chatbot and voice assistant solutions. Built on Node.js and JavaScript, it provides core modules for dialog management, context-aware memory, and third-party API integration, enabling dynamic tool usage during conversations. Developers can define custom skills, leverage large language models for natural language understanding, and integrate speech-to-text and text-to-speech engines for voice-enabled experiences. Jaaz’s modular architecture simplifies deployment across cloud and on-premise infrastructures, supporting rapid prototyping and production-grade workflows.
    Jaaz Core Features
    • Multi-turn dialog management
    • Context-aware long-term memory
    • Plugin-based tool and API integrations
    • LLM connectors (OpenAI, local models)
    • Speech-to-text and text-to-speech modules
  • Web platform for building AI agents with memory graphs, document ingestion, and plugin integration for task automation.
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    What is Mindcore Labs?
    Mindcore Labs provides a no-code and developer-friendly environment to design and launch AI agents. It features a knowledge graph memory system that retains context over time, supports ingestion of documents and data sources, and integrates with external APIs and plugins. Users can configure agents via an intuitive UI or CLI, test them in real time, and deploy to production endpoints. Built-in monitoring and analytics help track performance and optimize agent behaviors.
  • A Python framework enabling AI agents to execute plans, manage memory, and integrate tools seamlessly.
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    What is Cerebellum?
    Cerebellum offers a modular platform where developers define agents using declarative plans composed of sequential steps or tool invocations. Each plan can call built-in or custom tools—such as API connectors, retrievers, or data processors—through a unified interface. Memory modules allow agents to store, retrieve, and forget information across sessions, enabling context-aware and stateful interactions. It integrates with popular LLMs (OpenAI, Hugging Face), supports custom tool registration, and features an event-driven execution engine for real-time control flow. With logging, error handling, and plugin hooks, Cerebellum boosts productivity, facilitating rapid agent development for automation, virtual assistants, and research applications.
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