Aurora (Arvo AI) vs FluidifyAI
Aurora, from Arvo AI, is genuinely open source under Apache 2.0, with LangGraph agents that investigate across AWS, Azure, GCP and Kubernetes and integrate with PagerDuty, Datadog and Grafana. Like Regen and Neuri, it's free to self-host, so this is another case worth crediting directly rather than pretending otherwise.
The FluidifyAI suite is Regen, Neuri, Reflex and Gills: on-call, root cause analysis, auto-remediation and a conversational interface, sharing one incident record. Where Aurora and FluidifyAI both give you the source code, the real difference is what's built around it.
What open source alone doesn't cover
Aurora's own repository describes it as agentic incident management and root cause analysis: it investigates, it doesn't page anyone or run an on-call schedule, and it doesn't execute or verify a remediation itself, per its GitHub description.
FluidifyAI's open-source tier covers both Regen for on-call and paging and Neuri for the investigation Aurora does, and the paid Business tier adds Reflex to actually generate, dry-run and apply the fix, plus Gills as a conversational layer across all of it, with pricing published up front.
| Metric | FluidifyAI | Aurora |
|---|---|---|
| Open source [source] | Yes, Regen and Neuri | Yes, Apache 2.0 |
| On-call and paging | Yes, via Regen | No |
| Automated remediation | Yes, via Reflex | No, investigation only |
Evaluating FluidifyAI against Aurora (Arvo AI)?
We'll walk through the exact comparison with you - feature by feature.