Self-host Raven on your own infrastructure.
One Docker Compose command. No telemetry, no callback to a vendor. Runs on anything from a 4-GB VPS to a Raspberry Pi 5.
System requirements
Raven runs comfortably on a modest VPS or a Raspberry Pi 5. The numbers below are guidance — the actual footprint depends on the embedding model and corpus size.
| Resource | Minimum | Recommended |
|---|---|---|
| CPU | 2 cores (x86-64 or ARM64) | 4+ cores |
| RAM | 4 GB | 8 GB+ (16 GB if running local LLMs) |
| Disk | 20 GB SSD | 100 GB+ for embeddings + objects |
| OS | Linux with Docker 24+ | Ubuntu 24.04 LTS or Debian 13 |
| Network | Outbound to your model provider | Same; or fully air-gapped with Ollama |
Five-minute quick start
One command brings up Raven, PostgreSQL with pgvector, Valkey, and the AI worker. Out of the box it points at Ollama on the host; swap in OpenAI/Anthropic by editing one env file.
# 1. Grab the production Compose file (canonical, pinned to main)
curl -fsSL https://raw.githubusercontent.com/ravencloak-org/Raven/main/docker-compose.yml \
-o docker-compose.yml
# 2. Generate secrets and start
docker compose up -d
# 3. Open the app
open http://localhost:8080
Full guide and edge / Raspberry Pi variants: github.com/ravencloak-org/Raven.
Upgrades and rollbacks
Every release is tagged with semver and ships its own migration plan. Upgrade in place with docker compose pull && docker compose up -d. Roll back by pinning the previous tag in your Compose file — migrations are forward-only but always backward-compatible within a minor version.
Subscribe to release notifications by watching the GitHub repo, or follow the release feed.
Community support
Self-hosted Raven is fully supported by the open community. Open an issue or a discussion on GitHub — the maintainers and other operators are usually responsive within a day.
- Bugs / feature requests: GitHub Issues
- Operational questions, pattern advice: GitHub Discussions
- Need a paid SLA? See Pro & Enterprise plans.