Serverless + AI DevOps · hackathon build

Your CI/CD has a doctor now.

Deploy Doctor watches your GitHub Actions, diagnoses every red build, and ships a ready-to-merge fix PR in seconds — so your team stops playing detective and gets back to shipping.

4.2s
Avg fix proposed
78%
Auto-resolvable
0
Context switches
acme/checkout-service · main
Build failing
Jest: retries webhook until success ✕
Deploy Doctor diagnosing
Fix PR opened
Re-run green
red → green in 4.2slive simulation

How it works

From red build to merged fix in three moves.

01
Detect

We ingest GitHub Actions webhooks (or simulated events) the instant a run fails.

02
Diagnose

An AI engine correlates logs, commit diff and repo memory to classify the root cause.

03
Fix

A unified-diff patch is generated and opened as a PR. Simulated re-run turns the build green.

Everything your pipeline is missing

Six things a good deploy doctor should do.

Live Pipeline Feed

Server-Sent Events stream every run in real time so you notice red builds the moment they happen.

AI Root Cause

Classifies every failure: flaky test, dependency, infra, YAML, lint/type — with a reasoning trace you can read.

One-Click Fix PR

Generates a unified-diff patch, opens a simulated PR, and replays the pipeline so you see it turn green.

Repo Memory (RAG-lite)

Every failure is fingerprinted. Recurring flakes get higher confidence and link to prior fixes.

Slack-style Feed

Diagnoses and fix PRs show up in an in-app Slack channel — deep-linking straight to action.

Confidence-Gated Auto-merge

Trust low-risk categories to auto-merge above your threshold. Never block on flakes overnight.

Avg fix proposed in 4.2s78% auto-resolvable0 context switches~18m saved per fix

Try the demo in 10 seconds

Open the dashboard, click Inject Failure and watch the red-to-green loop end-to-end. No API keys. No setup.

Launch Dashboard

Prove ROI to your lead

Built-in analytics show failures by category, mean-time-to-fix before/after Deploy Doctor, and hours saved.

See Analytics