For platform engineers
One binary for business ops, data pipelines, and AI agents.
You’re the team that ends up supporting three automation tools: n8n for business, Airflow for data, and some Python thing for agents. m9m collapses that into one runtime — without pretending the problems are identical.
What you get as the platform team
- Single binary, single deploy pipeline. 300 MB container, no required database, no Node runtime. CapRover, Fly, Nomad, ECS, Kubernetes — wherever.
- Multi-workspace isolation. Workflows, credentials, audit logs, and runs scoped per team or tenant.
- Git-based versioning. Workflows are JSON. Review them in PRs, diff them in CI, roll back by reverting.
- Prometheus + OpenTelemetry. One scrape endpoint, one tracing pipeline. No vendor add-ons.
- Audit logs. Every run, every node execution, every credential use — as structured events, not screenshots.
Failure modes we handle
- Engine crashes: workflows resume from the last checkpoint, not from scratch.
- Noisy tenants: per-workspace concurrency limits stop one team from starving another.
- Rogue agents: CLI nodes run in sandboxed namespaces with CPU, memory, and network caps.
- Credential leakage: credentials are encrypted at rest, scrubbed from logs by default, and audited on every use.
Embedding m9m in your own platform
If you’re building a product that needs workflow automation (a CRM, a data platform, an agent tool), m9m embeds as a library. Go, Python, and Node.js SDKs run workflows programmatically — your users never see m9m’s UI, they see yours.
Related
Need help shipping agents or migrating off n8n?
Neul Labs — the team behind m9m — takes on a limited number of consulting engagements each quarter. We help teams migrate n8n workflows, build custom Go nodes, sandbox AI agents in production, and design automation platforms that don't collapse under load.