Search Results for "teams"
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Showing 246 open source projects for "teams"
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Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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MCP Teams Server
An MCP (Model Context Protocol) server implementation
An MCP server implementation for Microsoft Teams integration, providing capabilities to read messages, create messages, reply to messages, and mention members, facilitating AI-driven interactions within Teams. -
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EventCatalog
Open source tool for documenting and exploring event-driven systems
...With built-in discoverability features, developers and stakeholders can quickly explore how services interact and identify dependencies. EventCatalog supports extensibility through APIs and integrations, allowing teams to adapt it to their workflows. By bringing structure and governance to distributed systems, EventCatalog reduces confusion and helps teams make informed decisions faster. It is widely used by organizations to simplify event-driven systems and improve communication across teams. -
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chat
chat web app for teams, sass with user management and ratelimit
...It is positioned as a collaborative chat platform rather than a single-user demo, which is reflected in its administrative structure, multi-user handling, and deployment-oriented documentation. The project supports OpenAI, Azure OpenAI, Claude, Gemini, and Ollama-hosted models, giving teams flexibility in how they connect model backends. Its feature set includes shareable static pages generated from conversations, searchable conversation snapshots, text file uploads, multimedia file support when the model allows it, and prompt management with shortcut-based access. The repository structure also points to both web and Flutter-based mobile components, suggesting a broader product surface than a simple browser-only interface. -
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Gate22
Open-source MCP gateway and control plane for teams
...By integrating with MCP-aware systems, Gate22 helps maintain security and compliance while enabling teams to scale agent-enabled workflows without losing observability into what actions are taken and why. It can be used to enforce fine-grained policies that restrict dangerous or unauthorized operations, track which agents are calling which tools, and record metadata for auditing and debugging. -
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Agent Control
Centralized agent control plane for governing runtime agent behavior
...The repository includes SDKs, a server, telemetry components, examples, and integrations for common agent frameworks. It is especially useful for teams building customer-facing, internal, or enterprise agents that need scalable runtime guardrails. -
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MCP Linear
MCP server that enables AI assistants to interact with Linear project
The MCP Linear server is a Model Context Protocol (MCP) implementation that enables AI assistants to interact with the Linear project management system through natural language. It allows users to retrieve, create, and update issues, projects, and teams within Linear, facilitating seamless integration between AI models and project management workflows. -
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OpenSpec
Spec-driven development (SDD) for AI coding assistants
...The project addresses the common issue where AI tools produce inconsistent results when specifications exist only in chat history. It introduces a structured workflow that encourages teams to agree on what should be built before implementation starts. OpenSpec integrates into development pipelines and acts as a source of truth for AI-assisted coding sessions. By separating intent from execution, it helps teams reduce ambiguity and improve reproducibility in AI-driven development. Overall, OpenSpec serves as an enabling framework for spec-driven software engineering in the age of AI coding tools. -
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Activepieces
Open Source AI Automation
Activepieces is an open-source automation tool designed to build workflows that connect different apps and services without requiring extensive programming knowledge. It’s tailored for technical and non-technical users alike, enabling teams to automate repetitive tasks using a visual editor and a large library of pre-built connectors. Activepieces can be self-hosted or used via a cloud deployment, making it flexible for teams of all sizes. It supports integrations with popular services like Slack, Google Sheets, and Discord, and allows users to create custom pieces to suit unique needs. ... -
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Harness
A meta-skill that designs domain-specific agent teams
Harness is a meta-skill framework designed to automate the creation and orchestration of domain-specific AI agent teams within Claude Code environments. Instead of manually defining agents and their behaviors, it generates specialized agents, assigns them roles, and produces the skills they need to execute tasks effectively. The system focuses on scaling agent-based workflows by dynamically assembling teams tailored to specific problems. It enables structured collaboration between agents, allowing them to divide work and operate in coordinated pipelines. ... -
Cut Data Warehouse Costs by 54%BigQuery delivers 54% lower TCO with exabyte scale and flexible pricing. Free migration tools handle the SQL translation automatically.
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Kiln
Open source platform for managing, testing, and deploying AI apps
...Its workflow-oriented approach helps teams move from experimentation to production by organizing assets and results in a consistent format. It is particularly useful for teams working with large language models who need visibility into how changes impact outputs and overall system quality. -
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Rill
Fast SQL-based BI tool for real-time dashboards and analytics
...Its BI-as-code model combines SQL, YAML configuration, Git version control, and CLI tools, allowing teams to build, manage, and deploy analytics workflows efficiently. Automatic data profiling and responsive query updates help users understand datasets instantly. Interactive dashboards come with opinionated defaults, so teams can focus on insights instead of setup, while metrics layers standardize business logic for consistent reporting across dashboards, APIs, and AI systems. -
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Google Research
This repository contains code released by Google Research
Google Research is a massive monorepo that hosts a wide range of research code released by Google Research teams across machine learning, artificial intelligence, robotics, natural language processing, and other advanced domains. Rather than being a single framework, the repository serves as a centralized collection of experimental projects, reference implementations, and reproducible research artifacts. It is intended primarily for researchers and advanced practitioners who want to explore cutting-edge techniques directly from the teams that developed them. ... -
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Monkey Code
Enterprise-grade AI programming assistant designed for R&D collab
...The system includes a comprehensive management panel that allows teams to audit, monitor, and control how AI participates in coding workflows, ensuring accountability and governance at scale. MonkeyCode also integrates automated code security scanning to detect vulnerabilities in both human-written and AI-generated code, reinforcing secure development practices. -
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Bionic GPT
Bionic is an on-premise replacement for ChatGPT
...The interface is intentionally familiar, offering a ChatGPT-like experience with customizable branding, fast Rust-based performance, and conversation history management. Beyond chat, Bionic focuses heavily on enterprise RAG by letting users create AI assistants that work with their own documents, share those assistants across teams, and configure embeddings, chunking, and system prompts through the UI. The platform supports a wide variety of document types, includes data isolation features for teams, and layers in security measures such as RBAC, row-level security in Postgres, strong content security policy settings, and minimal container builds. -
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Middleware
Open-source DORA metrics platform for engineering teams
Bring more visibility to your engineering pipeline, get the right data & actionable insights to unclog bottlenecks, ensuring smooth software delivery. -
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SwanLab
An open-source, modern-design AI training tracking and visualization
...The tool records training metrics, hyperparameters, model outputs, and experiment configurations so that developers can easily understand how different experiments perform over time. It provides a modern user interface for visualizing results, enabling teams to compare runs, track model performance trends, and collaborate on machine learning research. SwanLab supports both cloud and self-hosted deployments, allowing organizations to run the system privately or integrate it into shared development environments. The platform integrates with a wide range of machine learning frameworks including PyTorch, Transformers, Keras, and other widely used training ecosystems. -
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Future AGI
Open-source platform for evaluating, observing, and improving LLM
Future AGI is an open-source, end-to-end platform for evaluating, observing, protecting, and improving AI agent applications. It is built for teams that need more than basic tracing, combining evaluations, simulations, datasets, guardrails, gateway routing, and optimization in one feedback loop. The platform helps developers detect hallucinations, measure agent quality, monitor production behavior, and use evaluation results to improve prompts or workflows over time. It supports both cloud and self-hosted deployment models, making it useful for teams with different privacy, infrastructure, and compliance needs. ... -
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Pruna AI
Pruna is a model optimization framework built for developers
Pruna is an open-source, self-hostable AI inference engine designed to help teams deploy and manage large language models (LLMs) efficiently across private or hybrid infrastructures. Built with performance and developer ergonomics in mind, Pruna simplifies inference workflows by enabling multi-model orchestration, autoscaling, GPU resource allocation, and compatibility with popular open-source models. It is ideal for companies or teams looking to reduce reliance on external APIs while maintaining speed, cost-efficiency, and full control over their data and AI stack. ... -
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Kodus
AI code reviews, just like your senior dev would do
Kodus-AI is a framework for building, training, and deploying intelligent agents and models, especially focusing on practical AI workflows for businesses and automation. It provides a structured set of tools and abstractions that help teams design agent behaviors, orchestrate data pipelines, optimize inference, and integrate AI capabilities with applications or services. The platform often includes model management, scalable training workflows, and orchestration patterns that help teams move from research or prototypes to production-ready AI deployments. Through configurable pipelines and a focus on modularity, it supports experimentation while maintaining reproducibility and performance. ... -
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Kanwas
Shared context board for teams and agents
Kanwas is an open-source shared context board built for teams and AI agents working together in the same workspace. It gives people and agents a common canvas where documents, evidence, decisions, notes, tasks, embeds, and outputs can live side by side. Instead of scattering context across chats, documents, and disconnected tools, Kanwas turns messy collaborative work into a shared visual environment that both humans and agents can read and update. -
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Coze Loop
Next-generation AI Agent Optimization Platform
...The platform also includes automated evaluation capabilities that assess agent performance across multiple quality dimensions such as accuracy and compliance. Its observability layer captures detailed execution traces, enabling teams to understand how inputs, prompts, and tools interact during runtime. Designed as an extensible open-source framework, Coze Loop helps teams move beyond ad-hoc prompt experiments toward structured, production-ready AI agent operations. -
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Ruler AI
Centralize and sync AI coding rules across tools and projects
...Instead of maintaining separate configuration files for tools like GitHub Copilot, Claude, or Cursor, it stores all rules in a single .ruler/ directory and distributes them automatically. This reduces duplication, avoids inconsistent outputs, and keeps guidance aligned as projects evolve. Ruler supports nested rule loading, allowing teams to define context-specific instructions for different parts of a codebase. It also manages MCP server settings, automates .gitignore updates, and provides simple commands to initialize, apply, and revert configurations. Designed for teams using multiple AI agents, it improves workflow consistency, simplifies onboarding, and ensures all assistants follow the same standards across projects. -
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AIPex
AI browser automation assistant, no migration and privacy first
...Rather than treating AI as a separate helper, AIPex embeds AI capabilities into common tasks like scaffolding components, generating tests, analyzing code quality, and performing refactors, allowing developers to stay in flow while benefiting from model-assisted insights. It supports modular plugin architecture so teams can extend or customize how assistants behave based on project conventions, code standards, or tooling preferences. AIPex also includes orchestration pipelines that let teams define multi-step AI-driven transformations — for example, generating code then running validation, producing documentation, and opening change requests — all within a unified pattern. -
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CC Mirror
Create multiple isolated Claude Code variants with custom providers
...Rather than running a single global Claude Code installation, cc-mirror creates separate instances — each with its own config, session store, prompt packs, theme tweaks, and optional preloaded skills — so you can tailor different environments for specific tasks, teams, or experimentation without polluting your primary setup. It also includes an interactive terminal UI for discovering, creating, and launching these isolated variants with a single command, making setup and switching effortless. For teams, cc-mirror’s team mode brings shared task storage and coordinated multi-agent workflows using shared goals and task lists that agents can collaborate on; this is useful for scaling up agentic coding across complex projects. -
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Skills for coding agents
Skills for coding agents
BuilderIO Skills is a collection of small, composable skills for coding agents. It is made for teams that want agents to perform better in planning, review, orchestration, validation, documentation discipline, and clear communication. Instead of acting like a heavy process framework, it lets teams install only the skills they need and adapt them to their project. The catalog includes tools for visual planning, visual PR recaps, agent audits, plan comparison, autonomous execution, model orchestration, usage-limit management, final status recaps, and documentation-first development. ...