Webhooks, cron schedules, and app events trigger chains of nodes that fetch, transform, and route data: n8n is a workflow automation platform built around a visual, node-based editor. It ships with 400+ built-in integrations covering databases like Postgres, SaaS tools like Slack and HubSpot, and every major AI provider. When a pre-built node does not exist, the HTTP Request node calls any REST API, and the Code node runs JavaScript or Python inline, so you are never blocked by a missing connector. Workflows execute as directed graphs with branching, loops, error handling, and sub-workflows, and every run is logged for inspection and replay during debugging. It also includes LangChain-based nodes for building AI agents with tool calling and memory. Self-hosting on RepoCloud gives you unlimited workflow executions with no per-task pricing, and all data stays on your instance. Runs on Node.js with SQLite by default; add Postgres and Redis queue mode when you need to scale workers horizontally.

The most comprehensive open-source control plane for Hermes Agent — a full workspace combining AI chat, visual workflows, multi-agent orchestration, coding agent management, and platform channel integration in one self-hosted dashboard. Real-time chat streaming over Socket.IO connects to any OpenAI-compatible backend including Ollama, OpenAI, Anthropic, and custom endpoints with multi-session management, tool call expansion, inline file previews for HTML, PDF, DOCX, images, and source code, plus profile-scoped uploads and workspace attachments. The visual workflow builder provides a Vue Flow canvas for constructing DAG-structured pipelines with directed edges, conditional routes, approval gates, loops, and live execution with per-node status updates. Platform channel integration configures Telegram, Discord, Slack, WhatsApp, Matrix, Feishu, DingTalk, QQBot, WeChat, and WeCom bots from one page with credential management and per-platform behavior settings. Multi-agent group chat rooms enable real-time messaging with @mention routing, automatic context compression, and SQLite message persistence. The coding agent panel installs, launches, and monitors Claude Code and Codex with built-in terminal, session history, and file diffs. Usage analytics track token consumption, estimated costs, cache hit rates, and 30-day daily trends with model distribution charts. Kanban boards plan and track agent work alongside cron job scheduling for recurring tasks. Deploy via Docker, npm CLI, or desktop installer for Windows, macOS, and Linux. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Buzz delivers the first production workspace where humans and AI agents operate as cryptographically equal team members on a self-hosted Nostr relay. The Rust-based backend stores every message, code patch, CI result, review comment, and workflow step as a signed Nostr event in a unified PostgreSQL-backed event log with Redis pub/sub for real-time presence and S3/MinIO for media storage. The integrated Git forge implements NIP-34, turning feature branches into dedicated channels where patches, reviews, and merge decisions live alongside the discussion that produced them — eliminating the split between chat tools and code hosts. Through the open Agent Client Protocol, Buzz natively supports Goose, Anthropic Claude Code, and OpenAI Codex as first-class channel members with scoped permissions, their own audit trails, and the ability to create patches, run workflows, and orchestrate multi-step automations via YAML-defined triggers including message events, reactions, schedules, and webhooks. The Tauri-based desktop client runs on macOS, Windows, and Linux, while buzz-cli provides agent-first JSON I/O for headless automation. Deploy via Docker Compose with the production bundle in deploy/compose/, Railway one-click, or build from source requiring Rust 1.88+, Node 24+, and pnpm. Multi-community mode scopes tenant data by domain with NIP-42 Schnorr authentication, rate limiting, and hash-chain audit logging. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache 2.0 licensed.

Open a project in DooTask and your tasks appear as a Kanban board, a list, a Gantt timeline, or a calendar, with team chat and file sharing beside them. Start from a project or task template and set a task to repeat so each new occurrence links back to the original. Mention colleagues in project and task chats, add emoji, and keep messages protected with asymmetric encryption. Files from chats and tasks gather in a Collaboration Files section, and WebDAV lets you manage My Files and Shared Files from Finder or Explorer. Check the dashboard for what is overdue, due today, or coming up, while department heads switch to a team view charting overdue and incomplete tasks per member. Visit the App Store to install official apps for approvals, OKRs, AI assistants, OnlyOffice, Minder mind maps, and Drawio diagrams. Administrators can add custom apps from an archive, a URL, or a GitHub repository. Add an API key for ChatGPT, Claude, Gemini, DeepSeek, or Grok, or point to Ollama or any OpenAI-compatible URL, then type @AI Robot in a project chat to draft tasks. Log in on the web by scanning a QR code with the mobile app, or use an LDAP or Active Directory username. The free Open Source Edition covers three users; paid editions raise that to ten or unlimited. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. AGPL-3.0 licensed.

With nearly 16,000 GitHub stars, 5.7 million monthly PyPI downloads, and 400+ contributors, Dagster is the most widely adopted asset-centric data orchestration platform — replacing task-oriented schedulers like Apache Airflow with a declarative model where every pipeline is defined as Python functions producing data assets such as tables, datasets, machine learning models, and reports. The built-in asset graph provides automatic lineage tracking across your entire data platform, showing exactly how data flows from ingestion through transformation to downstream consumption in a single unified view. Declarative Automation goes beyond cron scheduling with event-driven conditions that intelligently trigger materializations based on upstream freshness, data quality signals, and dependency state. The integrated data catalog auto-generates documentation from asset metadata, ensuring it never drifts out of sync with production. Native first-class integrations connect dbt, Snowflake, BigQuery, Databricks, Fivetran, Airbyte, Spark, Great Expectations, Tableau, Power BI, AWS, GCP, and Azure without custom glue code. The web UI visualizes asset graphs, run history, schedules, sensors, and partitioned materializations with built-in alerting via Slack and PagerDuty. Dagster Pipes enables executing arbitrary code in external environments including Spark clusters, Kubernetes Jobs, and cloud functions. Deploy via Docker Compose on a single VM with separate containers for the webserver, daemon, and code locations, or use official Helm charts for production Kubernetes with K8sRunLauncher scaling each run as an independent Job. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache-2.0 licensed.

CRMs, project trackers, inventory tools - NocoBase is an open-source no-code/low-code platform for building business systems like these. Its architecture is data-model driven: you define collections and relationships first, then compose any number of interface blocks (tables, forms, kanban, charts) on top of the same model, so data structure is never coupled to a particular view. The core is a microkernel where every feature is a plugin, WordPress-style; you enable official plugins, install marketplace ones, or write your own as npm packages with server and client parts. Data sources include the main PostgreSQL or MySQL database, external databases, and third-party APIs - so you can build admin panels over existing production data instead of migrating it. Built-in infrastructure covers role-based permissions down to collection, record, and field level, workflow automation with approval steps and scheduled triggers, and audit logs; a one-click switch flips between usage and configuration modes. Because custom features live in isolated plugins with a documented lifecycle, core upgrades do not overwrite your customizations, and swapping UIs never requires data migrations since interfaces sit on independent models. Written in TypeScript on Node.js, Koa, and React under the AGPL license, it is light enough for one person to run and extend - and where no-code SaaS platforms charge per seat and per app, a self-hosted instance runs unlimited applications for unlimited users at hosting cost alone.

Edict is a multi-agent orchestrator that runs every AI request through a court-style chain: a crown prince agent triages it, a planning department drafts the work, a review department can veto the plan, and specialist ministries execute what survives. Casual chat gets a direct reply, while real commands become kanban tickets whose titles are scrubbed of file paths and metadata. A vetoed plan returns for rework; an approved one is dispatched in parallel to ministries for finance, documentation, engineering, compliance, infrastructure, and HR. Commands arrive through Feishu, Telegram, or Signal channels configured in OpenClaw. The dashboard shows cards by state with heartbeat badges and stop, cancel, and resume controls, plus a department monitor and a memorial archive that turns finished work into five-phase timelines you can copy as Markdown. Nine edict templates add parameter forms and cost estimates, an officials panel ranks agents by merit score while tracking token spend, and per-agent model switching restarts the gateway in about five seconds. Agent thinking, tool calls, and results stream live. A permission matrix limits who may message whom, illegal state jumps are rejected, and every transition lands in an audit log. Worked examples cover competitive analysis, code review, and weekly reports. Dashboard login protects the console, and a systemd unit keeps it running across reboots. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Enterprises requiring production-grade governance for long-running autonomous AI operations can rely on OpenGeni, a self-hosted orchestration platform with human-in-the-loop approvals, Connected Machine execution, and comprehensive audit replays. Operators can configure durable multi-turn workflows that execute continuously toward specified goals without premature termination, automatically pausing when human verification, structured multiple-choice decisions, or critical credential approvals are required. Teams can assign execution workloads across ephemeral cloud sandboxes or route them straight to enrolled Connected Machines to run commands directly against local code repositories without exposing inbound network ports. The integrated web console lets developers inspect live Server-Sent Event activity streams, replay complete turn histories from audit logs, inspect generated artifacts, and cancel or steer in-flight agent tasks on demand. Platform administrators can enforce fine-grained access policies through GitHub App repository bindings, broker temporary role-scoped secrets, and maintain a shared organizational knowledge base where agents propose findings for human review before vector indexing. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache-2.0 licensed.

Dify turns the notoriously complex process of building production-grade AI applications into a visual drag-and-drop experience that teams can actually ship and maintain. With over 87,000 GitHub stars and backing from prominent investors, the platform has become the go-to open-source LLMOps solution for organizations that refuse to be locked into proprietary AI stacks. The visual workflow canvas lets developers wire together LLM calls, conditional logic, iteration loops, tool invocations, and human-in-the-loop checkpoints without writing boilerplate integration code. Its RAG pipeline engine handles the full document lifecycle from ingestion of PDFs, Word documents, and HTML through configurable chunking strategies, embedding with models from OpenAI or open-source alternatives, vector storage in Weaviate, Qdrant, Pinecone, or pgvector, and hybrid semantic-plus-keyword retrieval with citation tracking. Dify integrates with hundreds of model providers including OpenAI GPT-4o, Anthropic Claude, Google Gemini, Mistral, Llama, and any OpenAI-compatible endpoint like Ollama for fully local inference. The agent framework supports both ReAct and function-calling strategies with 50-plus built-in tools spanning Google Search, DALL-E, Stable Diffusion, WolframAlpha, and custom API definitions. Published apps can be deployed as hosted web interfaces, embedded chat widgets, REST API endpoints, or MCP-compatible tools. Enterprise features include role-based access control, SSO integration, and audit logging. A built-in marketplace enables teams to share and reuse model providers, tools, and workflow templates across projects. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache 2.0 licensed with an open-source community edition.

Sim Studio lets teams build, deploy, and monitor AI agent workflows by dragging blocks onto a visual canvas and wiring them into executable pipelines, backed by over 1,000 integrations. The React Flow editor represents each step as a node: LLM calls, tool invocations, conditional branches, and data transformations form directed acyclic graphs that run as complete agent pipelines. Every major LLM provider works natively, including OpenAI, Anthropic, Google Gemini, Groq, and Cerebras, plus local models through Ollama and vLLM. Integrations span Gmail, Slack, Microsoft Teams, Telegram, WhatsApp, Notion, Google Workspace, Airtable, GitHub, Jira, Linear, Perplexity, Firecrawl, PostgreSQL, Supabase, Pinecone, and Qdrant. Built-in tables provide a database layer, a file store offers shared team storage, and knowledge bases powered by PostgreSQL with pgvector enable retrieval-augmented generation. Finished workflows deploy as REST API endpoints, scheduled jobs, or Slack bots, with block-by-block execution traces for full observability. Real-time collaborative editing via Socket.io supports simultaneous multi-user construction. Alternatively, describe agent behavior in natural language and Sim assembles the workflow automatically. Built on Next.js App Router, Bun runtime, Drizzle ORM, and Tailwind CSS. 29,400+ GitHub stars and 100,000+ builders. Apache-2.0 licensed.

Describe the task in plain words, pick the sources and model it may use, and an agent plans the workflow before running it. That is the core loop: agents build editable visual workflows from a task description, execute them on demand or on a schedule, and keep everything traceable. Prefer building by hand and the canvas offers 17 preconfigured steps, branching, undo and redo, JSON import and export, plus eight starter templates. Feed it real work by importing PDF, DOCX, XLSX, CSV, JSON, and text files, or by connecting folders, HTTP endpoints, and approved local programs. Upload a screen recording and it identifies the actions with timestamps, turning a demonstrated process into an editable workflow you can refine. Model calls go to the endpoint you choose: Ollama, LM Studio, vLLM, or any OpenAI-compatible service, local or cloud with your own credentials. Every run can be inspected step by step, cancelled mid-flight, and exported as JSON, CSV, or Markdown reports. Observations from completed runs land in a knowledge and learnings store, where you review them and promote the useful ones into reusable skills for the next task. The Docker release bundles the application with FFmpeg and local Whisper support, and your documents stay on your own machine. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache License 2.0 licensed.

Modern engineering teams and busy households deploy Octop to run private, autonomous AI agents equipped with persistent memory workspaces, scheduled cron jobs, and direct browser automation. Users can orchestrate specialist agents tailored for software development, IT operations, content generation, and system diagnostics through an interactive React dashboard. The platform connects directly to Discord, Feishu, DingTalk, and WeCom, allowing team members to delegate complex tasks without leaving their everyday messaging apps. An integrated remote desktop and browser control engine lets agents navigate websites, capture screenshots, fill forms, and operate graphical software autonomously. Administrators can assign distinct MBTI personality profiles to agents, establish granular role-based permissions, configure scheduled cron workflows, and integrate custom Model Context Protocol servers for external tool access. Long-term memory persists across conversations through dedicated workspace files, ensuring contextual continuity whenever switching between underlying language models or team collaborators. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

With over 77,000 GitHub stars accumulated in under five months since its March 2026 launch, Paperclip has become the default control plane for teams running multiple AI agents in production. Rather than juggling dozens of terminal tabs with Claude Code sessions, Codex instances, and Gemini CLI workers, Paperclip organizes all agents into a company structure with org charts, reporting lines, role-based permissions, and per-agent monthly budgets that trigger hard-stops when exceeded. The platform supports any runtime through its adapter system — Process adapters manage local CLI agents like Claude Code, Codex, Cursor, Pi, and OpenCode as child processes, while HTTP adapters trigger remote agents via webhooks to OpenClaw, serverless platforms, or custom endpoints. Heartbeat-based execution wakes agents on configurable schedules, injecting goal context, budget state, and workspace paths directly into the invocation payload. The Work and Task System provides atomic checkout with execution locks, first-class blocker dependencies, and structured work products to eliminate duplicate effort. Governance features include approval workflows, decision tracking, emergency stops, and full audit trails tracing every mutation to an actor. Deployment runs as a single Node.js process with embedded PostgreSQL locally or scales to external Postgres for production, installable in one command via npx paperclipai onboard. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

With over 46,000 GitHub stars and one of the largest communities in data engineering, Apache Airflow is the workflow orchestration platform that lets teams define, schedule, and monitor complex data pipelines as Python code through directed acyclic graphs. Airflow 3.x introduced a modernized architecture with a task execution API, the Language Task SDK for writing task implementations in Java and Go alongside Python, asset-based partitioning with FanOutMapper and FixedKeyMapper for data-driven scheduling, a first-class state store for tasks and assets, pluggable retry policies, and a redesigned React-based web UI built on FastAPI. The provider ecosystem ships 80+ packages covering AWS, Google Cloud, Azure, Snowflake, Databricks, Apache Spark, Apache Kafka, PostgreSQL, MySQL, MongoDB, Slack, HTTP, SSH, Docker, Kubernetes, and dozens more, enabling a single deployment to orchestrate jobs across multi-cloud and on-premises infrastructure. The scheduler supports cron expressions, timetable plugins, data-aware scheduling triggered by asset events, and dynamic task generation through Python loops and conditionals. Built-in operators include BashOperator, PythonOperator, DockerOperator, KubernetesPodOperator, and sensor operators that poll external systems. The web UI provides DAG visualization with Gantt charts, grid views, and graph views, task instance logs, SLA monitoring, connection and variable management, and role-based access control. Deployment options include standalone mode, Docker Compose with CeleryExecutor or KubernetesExecutor, Helm charts for Kubernetes, and managed cloud services. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache License 2.0 licensed.

Salesforce's platform model, 100% open-source (Apache 2.0): Corteza is a Go/Vue.js low-code platform developed under a foundation, so there is no open-core bait to grow out of. The heart is Corteza Compose: namespaces contain applications, modules define record structures the way Salesforce objects do, and a drag-and-drop page builder assembles record pages, list pages, dashboards, and charts from configurable blocks. Automation comes from a visual, BPMN-style workflow engine plus JavaScript automation scripts, so cross-application business logic - approval chains, field updates, notifications - is configured rather than programmed. Granular role-based permissions reach down to individual modules, fields, and records, mirroring real organizational hierarchies. Corteza CRM ships as the flagship application built entirely on Compose: leads, accounts, opportunities, campaigns, and cases with a 360-degree customer view, covering most Salesforce standard objects - and because it is just a Compose app, adding or reshaping modules is configuration, not a fork. Everything is reachable over REST APIs, deliberately familiar tooling eases Salesforce admin migration, and a CLI can even generate synthetic records for load-testing what you build.

With 4,500+ GitHub stars and version 1.0.92 released August 2026, xyOps delivers a complete operations platform that unifies workflow automation, job scheduling, server monitoring, alerting, and incident response in one self-hosted system. The platform uses a distributed architecture where a central conductor coordinates lightweight xySat satellite agents running on Linux, macOS, or Windows worker nodes via persistent WebSocket connections. The visual workflow builder lets you chain events, triggers, actions, and monitors into multi-step pipelines with conditional logic, fan-out/fan-in parallelism, multiplex controllers for fleet-wide execution, and configurable resource limits. QuickMon provides per-second CPU, memory, disk, and network visibility streamed live to the web UI, while user-defined monitor plugins sample metrics every minute with time-series storage at hourly, daily, monthly, and yearly resolutions. Alert triggers evaluate expressions against live data and fire notifications via email, webhook, or custom actions, with full server snapshots attached showing every running process, network connection, and resource utilization at the moment of detection. Failed jobs and alerts automatically create tickets with linked logs, metrics history, and context for end-to-end incident tracking. The plugin marketplace supports extensions written in any language, and the Docker plugin enables container-based job execution. Deploy via Docker with persistent volumes on port 5522 for the web UI and 5523 for API access, running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. BSD-3-Clause licensed.

With over 3,700 GitHub stars and growing adoption among teams tired of managing complex orchestration platforms, Dagu delivers a complete workflow engine as a single Go binary that requires no external database, message broker, or framework installation. Define directed acyclic graphs in declarative YAML — specifying dependencies, schedules, retries, timeouts, approvals, and notifications — while keeping existing shell scripts, containers, and tools completely unchanged. The built-in Web UI provides live pipeline visualization, per-step log streaming, run history browsing, artifact previewing, manual retry controls, and workflow YAML editing without SSHing into servers. Execute steps as shell commands, Docker containers, Kubernetes Jobs, SSH remote commands, SQL queries, or HTTP requests, with conditional branching and parallel execution handled natively. The integrated Model Context Protocol server exposes dagu_read, dagu_change, and dagu_execute tools, enabling AI agents like Claude, Codex, and Cursor to inspect workflow state, preview YAML modifications, and control runs through authenticated endpoints. The harness.run executor lets external coding-agent CLIs operate inside DAG steps with full scheduling and approval gate support. Scale beyond a single machine with the distributed worker mode, which dispatches tasks to remote nodes via gRPC with automatic label-based routing and worker selection. Deploy with Docker, the official Helm chart for Kubernetes, or a simple binary download requiring only a Linux, macOS, or Windows host. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. GPLv3 licensed.

An order that waits days for a payment or a manager's approval survives crashes, restarts, and deployments in Cadence, a workflow engine that resumes each process exactly where it stopped. Developers write the order's logic as ordinary Go or Java code. The engine records every step in an event history and replays it to rebuild state on any worker. Activities send the emails, call the APIs, and write the database rows, each with its own retry policy, timeout, and heartbeat. A durable timer waits seconds or months without holding a thread, a cron schedule launches recurring runs, and a signal delivers the payment confirmation into the running workflow. Queries read its state without changing it, child workflows split big processes into reusable parts, and versioning allows code changes while older executions are still in flight. Domains separate teams and applications, task lists carry their own rate limits and priorities, global domains replicate across clusters and fail over between them, and archival retains closed histories. Cadence Web finds executions with SQL-like queries, lays out event history as a grouped table or a timeline, and exposes payloads, pending activities, and stack traces. It can start, reset, signal, cancel, or terminate runs, with batch actions for thousands of workflows at once. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache-2.0 licensed.