Rootly vs. Resolve AI

Not by its own documentation. Resolve AI investigates alerts, answers questions in Slack and Teams, runs scheduled tasks, and can take approved actions such as silencing an alert or opening a pull request. Paging, escalation, incident declaration, and status pages come from other tools; its docs describe incidents being declared through PagerDuty, a Slack command, or a similar workflow, which Resolve then joins. Rootly runs all of that itself, with AI SRE built in.

Both investigate alerts across your telemetry and code, show their reasoning, and wait for human approval before changing anything. The difference is what each knows before it starts. Resolve AI builds its picture from telemetry and the knowledge your team curates for it: runbooks, docs, and retrospectives you add. Rootly AI SRE runs inside the platform that pages your team and runs your incidents, so the service catalog, on-call schedules, and every past incident are already its context.

Only for team membership. Resolve AI’s docs list Rootly as a source it can sync team rosters from with an API key. They describe no integration that sends Rootly alerts, incidents, or catalog data to Resolve, so an investigation there doesn’t see your Rootly incident history.

For most stacks, yes. Rootly AI SRE connects to Datadog, Grafana, New Relic, Sentry, Splunk, Dynatrace, GitHub, and more, with read-only access. Telemetry is the input both products share; Rootly adds the incident context around it.

If your team plans to keep a separate paging and incident tool, wants an investigation layer on top of it, and runs telemetry backends Rootly doesn’t connect to yet, Resolve AI’s broad connector list and in-cluster Satellite are worth evaluating. Teams usually choose Rootly when they want the investigation, the paging, the response, and the learning to share one record of every incident.

Both are read-only by default. Resolve AI can silence alerts, open pull requests, and dispatch GitHub Actions after a human approves, and its docs let an admin opt an individual tool into automatic execution. Rootly AI SRE investigates, suggests fixes, and drafts updates, and every change needs explicit human sign-off before it runs.

Yes. The Rootly MCP server brings incidents, on-call, and past fixes into Claude Code, Codex, Cursor, or any AI that speaks MCP, and a Claude Code plugin adds commands for responding, asking, checking on-call, and drafting retrospectives. AI SRE can hand a fix to Claude Code, Codex, Cursor, or Devin and get back a pull request linked to the incident. You can also connect your own MCP server and choose which of its tools Rootly AI may call.

Neither does, by their own policies. Rootly enforces zero third-party model training: your incident data is used only for your organization, never pooled with other customers. Resolve AI’s docs say it does not train on customer data.

As described in Resolve AI’s docs in October 2026, it bills for the work it does in credits: chats, investigations, incidents, and triages each draw on them, and it publishes no list prices. Its free trial allows 20 chats or investigations a day for 14 days. Investigations that start automatically from alerts draw credits too, so alert volume sets much of the bill.

Incident Response is $20 and On-Call is $20 per user per month. AI SRE requires Incident Response and is priced on request, Enterprise pricing is custom, and the free trial typically lasts two weeks. Eligible startups save up to 50%, and companies under 25 employees pay what they can, starting at $1. See Rootly pricing.

Yes. Rootly takes alerts from PagerDuty and other paging tools, so AI SRE can investigate while a team keeps its current pager. Teams that move paging to Rootly too are usually live within a week, with dual-running during the transition.