Search Results for "multi language"
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Showing 4 open source projects for "multi language"
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GoClaw
GoClaw is OpenClaw rebuilt in Go
GoClaw is an enterprise AI agent platform that rebuilds OpenClaw in Go for stronger concurrency, simpler deployment, and production-oriented multi-agent orchestration. It acts as a gateway that connects language models to tools, channels, memory, and organizational data through a single binary. The platform is built for teams that need multiple agents to collaborate, delegate tasks, and operate across different providers without losing tenant isolation. It supports more than 20 LLM providers and several communication channels, making it flexible for internal automation, customer-facing assistants, and agent operations. ... -
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HiClaw
An open source collaborative multi-agent OS
HiClaw is an AI-powered legal assistant framework developed within the AgentScope ecosystem to support intelligent legal reasoning, document analysis, and workflow automation for legal research and compliance tasks. The project combines large language models with agent orchestration systems to process legal documents, interpret regulations, summarize contracts, and assist with legal knowledge retrieval. It is designed to provide structured, explainable workflows that help legal professionals... -
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Klavis AI
MCP integration platforms for AI agents to use tools at any scale
Klavis AI is a Y Combinator X25-backed open-source infrastructure platform that enables AI agents to reliably connect with external tools and services at scale through Model Context Protocol (MCP). Founded by ex-Google DeepMind and ex-Lyft engineers, Klavis provides 50+ production-ready MCP servers with enterprise OAuth support for GitHub, Slack, Gmail, Salesforce, Linear, Notion, and more. The flagship product Strata solves tool overload through progressive discovery, achieving +13% higher... -
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Coze Loop
Next-generation AI Agent Optimization Platform
Coze Loop is a developer-oriented platform that provides full lifecycle management for AI agents, covering everything from prompt engineering to production monitoring. The project aims to simplify the increasingly complex workflow of building reliable AI agents by offering integrated tools for debugging, evaluation, observability, and optimization. Through its visual playground, developers can test prompts interactively and compare outputs across different language models. The platform also... -
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