Your always-on AI oncall engineer. The moment an alert fires, ZeroSev investigates your logs, metrics, traces and deploys, builds a cited root-cause hypothesis, and drafts the fix — so your first human minute is reviewing, not reading dashboards.
Hey hunters 👋 I'm Muru, building ZeroSev after a decade of building SRE systems.
Every on-call engineer knows the 2 a.m. page: you wake up, open five dashboards, and spend the first 20 minutes just reconstructing what happened before you can even start fixing it.
ZeroSev flips that. The instant an alert fires, it's already investigating and reading your logs, metrics, traces and recent deploys, cross-referencing a live map of your services, and building a root-cause hypothesis with cited evidence. By the time you join the call, there's a ranked hypothesis and a draft fix waiting. You review, ask follow-ups ("could it be Postgres instead?"), and approve. Nothing runs without your sign-off unless it's below an autonomy threshold you set.
What makes it different: it's stack-neutral. Bring your own model, keep your existing observability and paging (Datadog, Grafana, PagerDuty, whatever), run it on any cloud or self-hosted. No vendor lock-in, no weeks of baseline learning — it's responding to incidents on day one.
We're opening waitlist today to gather interest in the product and to help gauge what would make you trust an agent with the first look at an incident?
Zailoo
Mailwarm
Does ZeroSev open a PR or run remediation commands, or is it strictly suggestions with links to evidence?
Zailoo
@thamibenjelloun - Automatic corrections through PRs for human approval is definitely the direction are going for in v2.