All use cases
AUTOMATION

Close routine incidents without waking a human

The same five runbook patterns account for 60-80% of pages, and a human runs them by hand every time.

"When a known pattern fires, I want the agent to execute the matching runbook inside policy, log the action, and escalate to a human only if the action fails or the pattern is unfamiliar."

The problem

Routine remediation is the textbook case for automation: the same runbook pattern, run dozens of times per month, by a human at variable hours. The cost is two-fold. First, the cumulative human-time spent on toil. Second, the opportunity cost: every minute on a routine fix is a minute not spent on the work that compounds (postmortem fixes, capacity planning, automation of the next pattern). Toil compounds; reliability investment compounds in the other direction.

How Nova solves it

Nova's agent fleet runs runbooks in your environment with a trust score, a policy envelope, and a reversible audit trail. You decide what's autonomous and what's gated.

  1. Codify the runbook once

    Translate the existing runbook into Nova's machine-readable format, preconditions, actions, postconditions, rollback. The agent now has the recipe.

  2. Run in shadow mode first

    Nova proposes the action without executing it. You compare its choice to what the on-call would have done, build trust, then promote to autonomous.

  3. Trust scores gate autonomy

    The agent earns more autonomy as it proves out, hundreds of successful runs without rollback push the trust score up; a single rollback drops it. You set the threshold for autonomous vs human-gated.

  4. Always-on audit trail

    Every action is logged with the agent, the policy that allowed it, the inputs, and the outcome. Reversible by a single command if anything looks wrong in review.

Teams that promote a top-10 runbook set to agent-autonomous typically see 60-80% of pages closed without a human, with zero increase in incident-rate or rollback frequency.

Try this on your stack

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