$ systemctl status adoe.service
Active · L1 incident-response agent · v0.1.0

// adoe

adoe

Stop being paged for things a script can fix.

Autonomous L1 incident response. Triages alerts, runs the runbook when it's confident, and escalates only what genuinely needs a human — with the trace already attached. Your team gets back to the work that actually moves the product.

Autonomous triage
Classifies and investigates every alert before it reaches a human.
Noise reduction
Dedupe, correlate, suppress chronic false positives. Wake people for real.
Smart escalation
When it pages you, it comes with hypothesis, evidence, and a proposed action.
Safe execution
Read-only first. Mutating actions wait for human approval. Always validated.
$ avg setup time: 15 minutes · plug-and-play · keeps your existing stack
→ request_access ping@adoe.ai · how it works ↓
tail -f /var/log/adoe/agent.log LIVE

// capabilities

Built for the operator, not the slide deck.

Every action is auditable, every escalation reproducible, every playbook editable. No magic — just a faster, calmer L1.

cap_01

Playbook matching

Every alert is fingerprinted and matched to a known SOP in milliseconds. Confidence scored, fully traceable.

cap_02

Safe remediation

Idempotent runbooks executed in a sandboxed runner. Blast-radius checks before any state-changing call.

cap_03

Human-in-the-loop

Anything ambiguous lands in an approval queue with diff, plan, and rollback ready for one-click review.

cap_04

Noise reduction

Correlates flapping signals across sources. Surfaces the noisiest alerts so you can fix the monitor, not the symptom.

cap_05

Source-agnostic

Webhook in, structured event out. Bring your existing monitoring stack — no rip-and-replace.

cap_06

Operator-first console

Forensic, dense, keyboard-driven. Built for SREs who live in tmux and read logs at 2am.

// pipeline

From webhook to resolution in four stages.

Every alert flows through the same deterministic pipeline. Each stage is observable, replayable, and fails closed.

step 01

Ingest

Webhooks from your monitoring stack normalized into a single event schema. Source-agnostic, signed payloads.

→
step 02

Match

Vector + rules engine resolves the alert to a playbook with a confidence score and linked history.

→
step 03

Execute

Sandboxed runner performs the runbook with pre-flight checks, dry-runs, and structured logs.

→
step 04

Escalate

Anything below the confidence floor opens a review with full context for a human operator.

// integrations

Plug in, don't replace.

Bring your existing monitoring stack. The agent normalizes events and writes outcomes back as comments, acknowledgements, and resolutions — wherever your team already works.

  • [01] Standard webhook + signed payload contract
  • [02] OpenTelemetry-compatible trace propagation
  • [03] Bidirectional sync with PagerDuty incidents
  • [04] Replays and dry-runs against historical alerts

Give your on-call the night back.

Open the console and watch the agent triage live alerts against your playbooks.

Launch console →