Search Results for "teams-for-linux"
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3765 projects for "teams-for-linux" with 2 filters applied:
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Forever Free Full-Stack Observability | Grafana CloudBuilt on open standards like Prometheus and OpenTelemetry, Grafana Cloud includes Kubernetes Monitoring, Application Observability, Incident Response, plus the AI-powered Grafana Assistant. Get started with our generous free tier today.
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$300 Free Credits to Build on Google CloudStart your next project with $300 in free Google Cloud credit. Spin up VMs, run containers, query petabytes in BigQuery, or build agents with Gemini Enterprise Agent Platform. Once your credits are used, keep building with 20+ always-free tier products including Compute Engine, Cloud Storage, GKE, and Cloud Run functions. No commitment required—just sign up and start building.
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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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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. ... -
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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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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. ... -
Our Free Plans just got better! | Auth0You asked, we delivered! Auth0 is excited to expand our Free and Paid plans to include more options so you can focus on building, deploying, and scaling applications without having to worry about your security. Auth0 now, thank yourself later.
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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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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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Open Scouts
AI-powered web monitoring platform
Open Scouts is an open-source platform designed to help organizations and communities manage volunteer resources, scout missions, and field operations with structured dashboards, task coordination tools, and reporting workflows. It brings together participant profiles, mission calendars, assignment tracking, and communication channels into one unified interface, enabling teams to plan events, assign responsibilities, and measure engagement without relying on disparate spreadsheets or manual tracking. Volunteers and team leads can log activity, submit reports, and visualize mission progress, while administrators gain oversight into coverage gaps, availability calendars, and participation trends. Open-Scouts emphasizes accessibility and flexibility, allowing groups of various sizes — from small nonprofit teams to larger field organizations — to adapt the platform to their workflows with custom roles, permissions, and event types. -
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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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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. -
Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
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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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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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Modelence
Modelence is an all-in-one TypeScript platform
Modelence is an all-in-one TypeScript platform aimed at helping teams ship production web apps with far less boilerplate than a typical full-stack setup. It positions itself as a Supabase-style experience tailored toward MongoDB-centric development, bundling common backend needs like authentication, database integration, and observability into a cohesive framework. The project is built to support modern application workflows where product teams want to move quickly without stitching together many separate services and libraries. ... -
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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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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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Jovo Framework
The React for Voice and Chat, build apps for Alexa, Google Assistant
The multimodal experience platform enables professional teams to build and run apps that work across smart speakers, the web, mobile, and more. Fully customizable and open source. The Jovo product ecosystem allows you to build, test, and run powerful experiences for voice, chat, and web platforms. From local development to production, Jovo allows you to build robust experiences, faster. Build across devices and platforms and use all supported modalities thanks to the Jovo output template engine. ... -
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AI-Codereview-Gitlab
GitLab automatic code review tool based on large models
...The system monitors GitLab repositories and analyzes commits or merge requests using AI models to identify potential issues, coding mistakes, and quality improvements before the code is merged. By leveraging multiple large language model providers—including OpenAI, DeepSeek, ZhipuAI, or local models through Ollama—the platform allows teams to choose the AI engine that best fits their infrastructure and privacy requirements. When code changes occur, the system can automatically generate review comments and feedback that are posted directly into GitLab merge requests, allowing developers to see suggestions alongside human reviewer comments. In addition to code analysis, the tool can produce daily development summaries and notifications that help teams track progress and review activity across projects. -
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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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PromptBin
A free guide for learning to create ChatGPT3 Prompts
...At its core, the project acts as a curated and structured library of prompts across a wide variety of use cases, including writing, brainstorming, debugging, and coding, making it particularly useful for both beginners and advanced users. The repository is also intended as a foundation for building custom prompt management systems, allowing developers or teams to fork and adapt it into internal tools or client-facing solutions. It includes a simple front-end interface that enables searching, filtering, and copying prompts quickly, emphasizing usability and accessibility. Beyond just a static list, the project embodies best practices in prompt engineering by demonstrating how structured inputs can significantly improve AI outputs. -
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Astron Agent
Enterprise platform for building and orchestrating AI agent workflows
...It also integrates robotic process automation capabilities so agents can execute tasks across digital systems instead of only generating responses. Astron Agent supports scalable and high-availability deployments, allowing teams to run reliable AI agent infrastructure in distributed environments. It includes collaboration features that allow teams to develop, manage, and operate AI applications together. With its extensible architecture and enterprise-focused design, it aims to help organizations build production-ready intelligent agent solutions. -
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Remotion
Make videos programmatically with React
...Because it integrates with the React ecosystem, Remotion fits naturally into modern front-end stacks and tooling, and can produce dynamic content like personalized videos, dashboards, and data-driven animations with the same code used to build interactive web apps. The framework supports exporting to standard video formats, audio synchronization, frame callbacks, and powerful tooling for previewing and debugging, so teams can iterate quickly and reliably. -
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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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Polyaxon
MLOps tools for managing & orchestrating the ML LifeCycle
Polyaxon is an open-source machine learning operations (MLOps) platform built to help individuals, teams, and organizations develop, train, orchestrate, and monitor machine learning and deep learning workflows at scale with reproducibility and automation as core principles. It provides a unified solution for tracking experiments, managing datasets, scheduling jobs, and comparing results across runs, which greatly improves productivity and collaboration in data science teams. -
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ZAPI
ZAPI by Adopt AI is an open-source Python library
ZAPI is a developer-centric API framework that streamlines building, testing, and deploying APIs with strong type safety and minimal boilerplate, helping teams deliver backend services faster with fewer errors. It emphasizes a declarative router and schema model that uses types to define request and response formats, providing clear contracts for frontend and backend teams while automatically generating documentation. Zapi abstracts many repetitive tasks such as validation, authentication flows, and error handling so developers can focus on business logic instead of infrastructure plumbing. ... -
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DeployStack
Centralized credential vault, governance, and token optimization
...The project emphasizes repeatability and clarity, enabling teams to follow best practices for scalability, security, and operational reliability without hand-crafting deployment scripts for every new service. It supports integration with popular cloud providers and infrastructure tooling, streamlining workflows that span local development through staging and production environments. -
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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. ...
