kossakovsky/n8n-install — 🚀 Self-hosted AI automation platform.

Description and use

**Brief Summary (2‑3 sentences)**
kossakovsky/n8n‑install is an open‑source, one‑command installer that spins up a self‑hosted AI automation stack—including n8n, Ollama, Flowise, RAG services, Supabase and 30+ auxiliary tools—behind automatic HTTPS. It gives teams a free, Zapier/Make‑style workflow engine that can index internal knowledge bases and power AI assistants with up‑to‑date, searchable context.

**Value**

• **Unified knowledge‑as‑code**: By bundling RAG components (vector DB, embeddings, document loaders) with a low‑code workflow engine, the project lets organizations turn static docs, tickets, or wikis into searchable, query‑able knowledge that AI assistants can cite.
• **Rapid AI automation**: Developers can create end‑to‑end pipelines (e.g., “when a new ticket arrives → embed → store → trigger a response”) without wiring dozens of services manually.
• **Cost‑effective alternative**: It replaces commercial Zapier/Make and proprietary RAG platforms with a free, self‑hosted stack, giving full control over data privacy and scaling.

**Practical Adoption Path**

1. **Spin‑up** – Clone the repo and run the provided shell script (./install.sh). The script provisions Docker containers for n8n, Ollama, Flowise, Supabase, and the chosen vector store, automatically obtaining TLS certificates via Let’s Encrypt.
2. **Configure data sources** – Connect your existing knowledge repositories (Confluence, SharePoint, Git, PDFs, etc.) using the pre‑built n8n nodes or Flowise UI; the installer already includes connectors for the most common sources.
3. **Build RAG workflows** – Use n8n’s visual editor to chain document ingestion → embedding (via Ollama) → storage → retrieval → LLM inference. Export the workflow as JSON for version control and CI/CD.
4. **Secure & monitor** – Leverage the built‑in Supabase auth for user management, enable role‑based access in n8n, and hook up Prometheus/Grafana dashboards (already containerized) for observability.
5. **Scale** – Because each component runs in its own container, you can horizontally scale the vector store or LLM inference nodes on Kubernetes or a cloud VM farm as load grows.

**Production‑Readiness**

• **Activity & community**: 890 ★, 229 forks, recent commits (last updated 2026‑06‑27), and a vibrant issue/PR discussion indicate an active maintainer base.
• **Maturity of components**: All core services (n8n, Ollama, Supabase, Flowise) are production‑grade and widely used in enterprise settings.
• **Installation robustness**: The installer automates TLS, health checks, and container orchestration, reducing manual setup errors.
• **Observability & security**: Built‑in support for Supabase auth, HTTPS, and optional monitoring stacks gives a solid baseline for compliance.
• **Remaining checks**: A final audit of the license (MIT/Apache‑compatible) and a security scan of the Docker images are advisable, but no major risks have been flagged.

Overall, kossakovsky/n8n‑install offers a high‑confidence, low‑friction route to deploy a self‑hosted AI automation platform that can be piloted today and scaled to production with minimal additional engineering effort.

Problem

kossakovsky/n8n-install helps make internal knowledge searchable and usable by assistants.

Outcome

High for an OSS candidate: recent activity, adoption, and ecosystem signals are strong enough for a serious pilot.

Workflow

• index knowledge bases
• improve search over documents
• ground assistant answers

Evidence

🚀 Self-hosted AI automation platform. Deploy n8n, Ollama, Flowise, RAG, Supabase & 30+ tools with one command. Auto HTTPS. Free Zapier/Make alternative.

Source