AI Site Reliability Engineering

The AI SRE that
shows its work.

Mirai watches every signal your stack already produces, collapses the noise into real incidents, and investigates them the way your best engineer would — then hands you a root cause with the evidence attached, and a fix it will not run until you say so.

Reads your telemetry. Writes nothing to production without an approval.

app.miraisre.com/incidents
Mirai SRE incident console showing an active SEV1 with an AI-generated root cause at 96% confidence and an autonomous investigation timeline.
Sits on the stack you already run Prometheus Datadog Grafana OpenTelemetry CloudWatch Kubernetes PagerDuty GitHub Slack
The problem

On-call doesn't fail because
your team lacks skill.

It fails because the signal is buried, the context lives in six tools and three people's heads, and the clock starts at 3am. Every minute spent reconstructing what happened is a minute not spent fixing it.

98%

Alerts that mean nothing

Most of what a monitor emits is a duplicate, a symptom of something already known, or a threshold nobody has revisited in two years. Humans pay the interrupt cost anyway.

47m

Spent finding, not fixing

The bulk of an incident is archaeology — pulling dashboards, diffing deploys, hunting the trace. The actual remediation is often a one-line revert.

1 in 3

Engineers considering leaving

Pager fatigue is the quiet attrition tax on every platform team. The people who hold the most context are the ones who get woken up the most.

Figures reflect widely reported industry patterns in site reliability engineering, not measurements from a specific customer.

The platform

An engineer's workflow, running continuously.

Mirai is not a summarizer bolted onto your alert feed. It reasons over your topology, your change history and your past incidents — and it is auditable at every step.

Signal correlation

Deduplicates, groups and time-aligns alerts across every source into one incident with one owner — so forty pages become one, and the cause outranks the symptom.

Autonomous investigation

Ranks hypotheses, then tests them — querying metrics, traces, logs, the change feed and your incident archive in parallel, and discarding what the data doesn't support.

Evidence-backed root cause

Every claim links to the artefact that supports it — the diff, the metric series, the trace, the precedent. Ruled-out hypotheses ship with the verdict, so you can check the reasoning instead of trusting it.

Guarded remediation

Drafts the actual change — a PR, a rollback, a scale action — with blast radius, reversibility and change-window checks computed before a human is ever asked to approve it.

Runbooks that execute

Turns the procedure living in a wiki page or a senior engineer's memory into a versioned, parameterised runbook Mirai can propose, run and report on.

SLOs and error budgets

Burn-rate alerting that pages on user-visible harm rather than CPU graphs, with budget accounting that tells you when to ship and when to stop.

How it works

Connected in an afternoon.
Useful the same night.

01

Connect, read-only

Point Mirai at your observability stack, your repos and your incident tool using scoped, read-only credentials. No agents on your hosts.

~30 minutes
02

Learn the system

It builds a live service and dependency graph, ingests your change feed, and reads your closed incidents to learn how this estate actually fails.

first 7 days
03

Investigate everything

Every alert gets a full investigation — not just the ones a human has time for. Most close silently; the ones that matter arrive with a root cause already attached.

continuous
04

Act within policy

You define what Mirai may do, where, and who signs off. Autonomy widens per failure class only after that class has proven itself.

you hold the dial
Inside the product

Built for the moment it's 2am
and the graph is red.

Four views that carry an incident from noise to resolution.

app.miraisre.com/incidents/INC-2291
Incident console: an active SEV1 on checkout latency with a 96%-confidence root cause, supporting evidence chips, a proposed fix awaiting approval, and a timestamped autonomous investigation timeline.

One incident, not forty alerts

Forty downstream alerts collapse into a single SEV1 with one owner. The root cause, its confidence, the signals that support it and the ones Mirai ruled out are on the first screen — alongside the fix it has already drafted. One human was paged instead of four.

app.miraisre.com/root-cause/INC-2291
Causal chain view: a deploy that shrank a connection pool traced through pool saturation, blocked threads and service latency to checkout SLO burn, with linked evidence and a p99 latency chart.

A causal chain you can audit

Cause to business impact, reconstructed from traces, metric series and change events — with each link backed by a citation you can open. The ruled-out hypotheses are published too, because a root cause you can't falsify isn't an answer.

app.miraisre.com/signals
Signal and noise dashboard: a funnel from 1.44 million raw signals down to 148 human pages, a weekly pager-load chart, the noisiest monitors, and mean-time-to-root-cause metrics.

Prove the noise is actually gone

The full funnel from raw signal to human page, per week and per monitor — plus the monitors that have never once preceded a real incident, with a recommendation to demote them. Reliability work you can put in front of a board.

app.miraisre.com/remediation
Remediation approval screen: a proposed configuration revert shown as a diff, six guardrail checks, the autonomy policy matrix by environment, and an immutable audit trail.

The fix, and the reason you can trust it

The exact diff, the guardrails that passed, the policy that requires your signature, and an immutable audit line for every action taken. Destructive classes — schema, IAM, data deletion — are never delegable, in any environment.

Screenshots show a reference environment with representative data.

Governed autonomy

Autonomy is a dial,
not a switch.

The honest state of this field in 2026 is that fully autonomous production operations aren't trustworthy yet — and vendors who claim otherwise are selling you their risk. Mirai earns scope one failure class at a time, and every widening is a decision you make, log and can revoke.

  • Read-only by default. Write access is granted per action type, per environment.
  • Your data stays yours. Never used to train shared models. Deployable in your VPC or ours, with India, EU and US residency.
  • Immutable audit trail. Every read, hypothesis, proposal and action — exportable for audit and post-incident review.
  • SSO, SAML and RBAC from day one, with approval routing that follows your existing change-management policy.
  • Confidence routing. Below your threshold, Mirai escalates to a human instead of guessing.
L0ObserveCorrelate and enrich. Nothing acts.default
L1InvestigateFull RCA on every alert, all environments.auto
L2Act in non-productionRestart, scale, roll back in dev and staging.auto
L3Act in production, on approvalDrafts the change; a named human signs it.approve
L4Autonomous, per proven classOnly failure classes with a verified track record.opt-in
Schema, IAM, data deletionNot delegable. In any environment. Ever.never
Reliability services

Half of reliability is the platform.
The other half is the work.

Mirai SRE's engineering practice takes on the reliability programme itself — for teams modernising a hybrid estate, standing up SRE for the first time, or trying to make an observability spend actually pay for itself.

Talk to an engineer
Reliability assessment
A structured read of your architecture, incident history and toil, ending in a prioritised remediation plan with effort and impact attached.
SLO & error-budget programme
Service-level objectives your product org will actually agree to, wired into alerting and release policy rather than a slide deck.
Observability re-platforming
OpenTelemetry standardisation, cardinality and cost control, and instrumentation that answers questions instead of producing graphs.
On-call transformation
Rotation design, escalation policy, runbook coverage and blameless review — the operational fabric that makes automation safe to trust.
Hybrid & VMware-to-cloud reliability
Deep operational experience across VMware Cloud Foundation, vSphere estates and public cloud, for platforms that live in both worlds.
Get started

See it investigate
your last incident.

Send us an incident you've already closed. We'll connect Mirai read-only, let it investigate from scratch, and show you what it found against what actually happened.

Prefer email? ratna@miraisre.com

Opens your mail client addressed to ratna@miraisre.com. We reply within one business day.