Technical teams, developers, and privacy-conscious operators who need full code ownership, no vendor lock-in, and data sovereignty require an automation stack built entirely on open-source tools. This stack provides workflow automation, LLM orchestration, AI agent frameworks, and vector search — all self-hosted and free to use.
n8n handles all workflow automation on self-hosted infrastructure with full code access for custom integrations. Flowise and Dify provide visual interfaces for building LLM pipelines, RAG applications, and AI chatbots. CrewAI manages multi-agent orchestration where complex AI task delegation is needed. Activepieces provides an alternative automation layer for teams preferring its interface.
A basic setup (n8n + Dify + Flowise) runs on a 2 vCPU / 4GB RAM VPS ($10–20/mo on Hetzner or DigitalOcean). For LLM inference on-device rather than calling external APIs, you need 16GB+ RAM and ideally a GPU. Most setups call external LLM APIs (OpenAI, Anthropic via API) rather than running models locally.
Yes. Both Flowise and Dify support Ollama as a local LLM provider. n8n's AI nodes can connect to any OpenAI-compatible endpoint, including Ollama. This enables fully local AI processing with no external API calls for maximum data privacy.
n8n is more mature with 400+ integrations and a larger community. Activepieces is newer with a cleaner UX but fewer integrations. Both are actively developed open-source projects. Most teams default to n8n; Activepieces is a strong alternative if you prefer its interface or need its specific integrations.