Agentic L1 incident response

Your first responder for every production incident.

ADOE investigates alerts, executes approved runbooks, and escalates only when human judgment is required — with the full audit trace already attached.

80%alert-noise reduction 70%incidents auto-resolved 4-minmedian resolution

Works with the tools your on-call team already uses

Grafana Prometheus PagerDuty Splunk Sensu Slack AWS Kubernetes GitHub

Outcomes

Fewer pages. Faster resolution. Hours back.

What teams see when ADOE takes first watch. Figures reflect current deployments and are configurable to your environment in the calculator below.

80%Alert-noise reductionDedupe, correlation, and suppression of chronic false positives.
70%Incidents auto-resolvedConfident, verifiable playbook matches resolved without paging a human.
4-minMedian resolutionAlert-to-verified for auto-resolved incidents.
~0.7FTE recovered / 10 engEstimate yours →

Watch an incident resolve

One incident, start to finish.

A latency alert on a Kubernetes service after a bad deploy. Step through exactly what ADOE does — and where it stops for a human.

How ADOE works

An operational pipeline, not a black box.

Every alert flows through six stages. Each stage has a defined input, agent action, safety boundary, and result.

01

Ingest

Input
Alerts from every monitoring source
Action
Normalize, deduplicate, correlate into one incident
Safety
Read-only
Result
A single, deduplicated incident
02

Investigate

Input
The incident + context (deploys, logs, topology)
Action
Gather evidence, form a root-cause hypothesis
Safety
Read-only tools only
Result
Hypothesis + confidence + blast radius
03

Decide

Input
Hypothesis + available playbooks
Action
Match a runbook; choose execute / recommend / escalate
Safety
Confidence threshold gate
Result
A decision with reasoning
04

Act

Input
The chosen remediation
Action
Run it through your own executors
Safety
Approval for mutating actions
Result
An executed, logged action
05

Verify

Input
The action + the alert's own signal
Action
Poll the real metric to confirm recovery
Safety
Never false-resolve
Result
Verified resolution — or escalate
06

Escalate

Input
Anything unverifiable or low-confidence
Action
Page a human with hypothesis + evidence
Safety
Human judgment required
Result
A human, oriented in seconds

Capabilities

Built for the work on-call actually does.

◐

Autonomous triage

Classifies and investigates every alert with read-only tools before it ever reaches a human.

≈

Correlation & noise reduction

Dedupe, correlate, and suppress chronic false positives so people wake for real incidents.

⧉

Playbook matching

Maps incidents to your existing runbooks with a confidence score.

↻

Safe remediation

Runs approved actions through your own executors — GitHub Actions, SSM, SSH.

⎈

Human approvals

Mutating actions wait for a one-tap approval in Slack, with the plan and blast radius spelled out.

↑

Smart escalation

When it pages you, it comes with a hypothesis, the evidence, and a proposed next step.

▤

Audit trails & replay

Every decision and action is recorded, reproducible, and reviewable after the fact.

▣

Operator-first console

A calm incident view built for the people who own production.

Safety & human control

Autonomy you can actually trust with production.

The hard part of autonomous ops isn't acting — it's knowing when not to. ADOE is built so a VP of Engineering will let it touch prod.

✓
Read-only investigationTriage uses only read tools. Nothing mutates without a decision.
✓
Confidence thresholdsBelow the bar, ADOE recommends instead of acting.
✓
Approval-required actionsMutating steps wait for a human tap.
✓
Role-based permissionsScope what ADOE can see and do, per team.
✓
Pre-flight checks & dry runsValidate an action before it runs for real.
✓
Blast-radius checksEvery proposed action is scoped and labelled by impact.
✓
Rollback plansRemediations carry a defined way back.
✓
Post-action verificationConfirms recovery against the real signal — never false-resolves.
✓
Full audit historyEvery step is logged, attributable, and replayable.
✓
Tenant isolationYour data and credentials stay yours.

Integrations

Plug in. Don't rip and replace.

ADOE works with the stack your team already runs. Connect your sources and executors — nothing to migrate.

ROI calculator

Estimate the time and money ADOE returns.

Enter your environment. Everything recalculates instantly. Assumptions are shown and editable in the formula below.

Assumes $150k fully-loaded SRE · ~1.5 hrs × 2.5 responders per incident · 70% auto-resolved

⌥Your environment

engineers
1255075100

ADOE removes ~1.5 hrs of toil per incident through autonomous triage and resolution.

↗Estimated annual savings

1-year savings$98,438
2-year savings$196,875
6.6% of team capacity returned≈ 0.66 FTE across 10 engineers
1 YEAR
1,365 hrs
2 YEARS
2,730 hrs
How this is calculated — inputs vs. assumptions

You provide: team size, incident volume & cadence.

Assumptions (illustrative): $150,000 fully-loaded salary ÷ 2,080 hrs = hourly cost · 1.5 hrs × 2.5 responders of toil removed per incident · 70% of incidents auto-resolved.

hours = incidents/yr × 1.5 × 2.5 × 0.70  ·  savings = hours × hourly  ·  FTE% = (hours ÷ 2,080) ÷ team

Directional estimate, not a guarantee. Tune the assumptions to your own numbers.

Enterprise

Deploys into your world, on your terms.

Talk to the technical team about deployment, data handling, and controls for your environment.

Deployment

Runs against your existing monitoring and executors.

details on request
Data handling

Operates on your telemetry and credentials with tenant isolation.

details on request
Permissions

Role-based control over what ADOE can see and do.

Auditability

Full, replayable history of every decision and action.

Availability & support

Support expectations set with your team.

details on request
Security documentation

Available under NDA during evaluation.

contact us

Give your on-call team the night back.

See ADOE investigate and resolve a real incident against your own operational playbooks.