Comprehensive プロダクション対応 Tools for Every Need

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プロダクション対応

  • A Go SDK enabling developers to build autonomous AI agents with LLMs, tool integrations, memory, and planning pipelines.
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    What is Agent-Go?
    Agent-Go provides a modular framework for building autonomous AI agents in Go. It integrates LLM providers (such as OpenAI), vector-based memory stores for long-term context retention, and a flexible planning engine that breaks down user requests into executable steps. Developers define and register custom tools (APIs, databases, or shell commands) that agents can invoke. A conversation manager tracks dialog history, while a configurable planner orchestrates tool calls and LLM interactions. This allows teams to rapidly prototype AI-driven assistants, automated workflows, and task-oriented bots in a production-ready Go environment.
    Agent-Go Core Features
    • Pluggable LLM integrations (OpenAI, etc.)
    • Vector memory store for context retention
    • Configurable planning engine
    • Custom tool interfaces
    • Conversation manager
  • Modular AI Agent framework enabling memory, tool integration, and multi-step reasoning for automating complex developer workflows.
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    What is Aegix?
    Aegix provides a robust SDK for orchestrating AI Agents capable of handling complex workflows through multi-step reasoning. With support for various LLM providers, it lets developers integrate custom tools—from database connectors to web scrapers—and maintain conversation state with memory modules such as vector stores. Aegix’s flexible agent loop architecture allows the specification of planning, execution, and review phases, enabling agents to refine outputs iteratively. Whether building document question-answering bots, code assistants, or automated support agents, Aegix simplifies development with clear abstractions, configuration-driven pipelines, and easy extension points. It’s designed to scale from prototypes to production, ensuring reliable performance and maintainable codebases for AI-driven applications.
  • An open-source Python framework to build modular AI agents with memory management, tool integration, and multi-LLM support.
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    What is BambooAI?
    BambooAI combines a collection of modular Python libraries, utilities, and templates designed to streamline the creation and deployment of autonomous AI agents. At its core, BambooAI provides flexible memory architectures—vector databases, ephemeral caches—and configurable retrieval mechanisms for RAG workflows. Developers can easily integrate tools like web search, Wikipedia lookups, file operations, database queries, and Python code execution. The framework supports major LLM APIs (OpenAI, Anthropic) as well as local model hosting. Agents can be orchestrated via a simple CLI, a RESTful service, or embedded within applications. Logging, monitoring, and error recovery features ensure reliability in production. Community-driven extensions and plugin systems make BambooAI extensible for custom domains and workflows.
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