AI SRE comparison
WHAWIT vs Rootly
Both platforms coordinate the incident. The difference is what the AI is allowed to finish.
Short answer
Rootly and WHAWIT overlap more than most pairs on this site: both are incident-management platforms with native on-call, and both attach AI to the incident. The difference is what the AI is allowed to finish. Rootly's AI SRE surfaces root causes with confidence scores, highlights code diffs and drafts changes — and, in its own words, never auto-remediates without human sign-off. WHAWIT draws the human line at review rather than at execution: its agents hold scheduled shifts on the on-call roster, run approval-gated recovery actions against endpoints and MCP tools you connect, and ship the code fix as a tested pull request linked to the incident. If your team lives in Slack and wants AI-assisted coordination, Rootly is credible. If you want the incident to end with a merged fix, that is WHAWIT.
Side by side
| Capability | WHAWIT | Rootly |
|---|---|---|
| Incident management with timeline and postmortems | ||
| Native on-call: schedules, rotations, escalation policies | ||
| AI root-cause investigation with cited evidence | ||
| Reads your observability stack read-only | ||
| WhatsApp as a paging channel | ||
| AI agents with scheduled shifts on the on-call roster | ||
| Coding agent implements and tests the fix in a sandbox, opens the PR | ||
| Approval-gated infrastructure remediation | ||
| Itemized AI spend, per analysis, visible in the product | ||
| AI meeting bot transcribes incident bridges | ||
| Native mobile app with push notifications |
Based on each vendor's public documentation as of August 2026. Rootly is a trademark of its respective owner and is not affiliated with WHAWIT.
Where the products actually differ
Suggestion is where their loop ends — and where ours keeps going
Rootly's AI presents root causes and drafts changes for a human to act on. WHAWIT's coding agent takes the investigated incident, implements and tests the fix in a sandbox, and opens a review-ready pull request linked back to the incident. The human's job shrinks from "do the fix" to "review the fix".
Agents on the rotation, not just in the channel
WHAWIT's five-role agent team serves scheduled on-call shifts and investigates on its own cycle, opening deduplicated incidents with evidence before anything pages. Coordination bots respond to incidents; rostered agents reduce them.
Remediation that executes, gated by your rules
Operational fixes run as recovery actions — signed calls to endpoints and MCP tools you connect — behind approvals, severity thresholds, cooldowns and daily caps. You choose the autonomy level per action, not per vendor philosophy.
You can see what the AI costs
Every model call lands in a ledger itemized per analysis, visible in the product, with AI consumption passing through at cost. No bundled per-seat AI premium to reverse-engineer.
Questions teams ask
Is WHAWIT an alternative to Rootly?
Yes. WHAWIT covers the same platform surface — incident lifecycle, on-call schedules, escalation policies, Slack and Teams coordination — and extends the AI's reach: rostered agent shifts, approval-gated remediation, and code fixes delivered as tested pull requests.
What does Rootly have that WHAWIT does not?
Two honest gaps today: Rootly's AI meeting bot can transcribe live incident bridges into the record, and Rootly ships a native mobile app with push notifications. WHAWIT pages responders into the bridge — by voice call if needed — but does not ingest the call, and its mobile experience is a mobile-first web app.
Can we run WHAWIT alongside Rootly to compare?
Yes. WHAWIT connects read-only to your observability stack, so its agents can investigate the same incidents your current process handles. Score both on the bake-off rubric at whawit.ai/ai-sre before moving anything.
Run them side by side
Keep Rootly paging while WHAWIT investigates the same incidents. Compare the two on your own outages before you move a single rotation.