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CI/CD · Observability · Incident Response

One platform. Four capability modules. Ship in 9 minutes.

Yeinz replaces the six disconnected tools your delivery pipeline is held together with — a single binary, one source of truth, deployment cycles that used to take 47 minutes now finish before standup ends.

3.4×faster rollouts
9 minmedian deploy
4.2×median ROI
yeinz · deploy pipeline · main
$ yeinz deploy --service api-gateway --ref a3f9c2
→ resolving changeset... ok
→ running preflight checks... 14/14 pass
→ building artifact (38MB binary)... 2.1s
→ rolling out to 4 regions in parallel
00:00
build
00:02
test
00:05
canary
00:09
prod
✓ deployed to 4/4 regions · 8m 41s · 0 incidents
Four modules · one binary

What ships in the box.

No bolt-ons. No marketplace. Every Yeinz deployment ships with the same four modules wired into a shared event graph — pick which surfaces you turn on, drop the rest.

  1. 01

    CI/CD pipeline runner

    Hermetic build cache, parallelized test fan-out, and a deploy stage that pushes to four regions in under nine minutes. Single binary, 38MB.

    • YAML or TypeScript pipeline definitions
    • Hermetic cache hit-rate ~84% median
    • Native progressive delivery (canary, blue/green, feature-flagged)
  2. 02

    Unified observability

    Traces, logs, and metrics on the same timeline as your deploys — no agent zoo, no second vendor to reconcile IDs with. Sample retention defaults are sane.

    • OTLP-native ingest, no proprietary SDK required
    • Auto-correlated deploy markers on every chart
    • Tail-sampling that keeps errors, drops the noise
  3. 03

    Incident response & on-call

    Pages, escalation policies, and a war-room surface that joins the relevant deploy, trace, and runbook the second a page fires. No tab-switching.

    • Schedule imports from PagerDuty / Opsgenie
    • One-click roll-back straight from the incident page
    • Postmortem draft seeded from real timeline data
  4. 04

    AI incident summarization

    The first CI/CD platform with native on-call summarization — used by 1,800+ teams. Reads your logs, traces, deploys, and runbooks, then writes the postmortem your on-call would have written at 3am.

    • Drafts executive summary, timeline, and root cause
    • Grounded in your data — no fabricated citations
    • SOC 2 Type II scoped: no customer data used for training
Deployment timeline · instrumented

47 minutes → 9 minutes. Here is what actually changed.

The drop isn’t from faster hardware or more parallelism alone. It comes from collapsing the four hand-offs between CI, artifact storage, deploy orchestration, and verification into a single directed graph. Below is a real timeline from a customer rolling a service to four regions.

Build Test Canary Prod rollout
deploy · api-gateway · a3f9c2 · 4 regions 8m 41s · 0 incidents
00:00.0
build · 0.6s
00:00.6
parallel test fan-out · 1.6s
00:02.2
artifact cache hit · 1.0s
00:03.2
canary 5% · synthetics · 2.6s
00:05.8
canary 50% · SLO probe · 3.1s
00:08.9
prod 100% · 4 regions · rollback armed
previous baseline (industry median): 47m 12s yeinz measured: 8m 41s delta: −38m 31s
Trust · compliance · uptime

The receipts your security review will ask for.

SOC 2

SOC 2 Type II

Audited annually. Report available under NDA from the trust center.

ISO

ISO 27001

Certified information security management across the platform and org.

99.99%

Platform uptime

Trailing 12 months. Live status at status.yeinz.net — no marketing edits.

4.8/5

G2 rating

Across 612 verified reviews from engineering teams in production.

Observability · native, not bolted on

Traces, logs, and metrics on the same timeline as the deploy that broke them.

Every Yeinz module writes to one shared event graph. So when a deploy ships and latency ticks up at 00:09:14, the chart, the trace, the log line, and the rollback button are already on the same screen — no cross-tool pivoting, no copy-pasting trace IDs.

  • OTLP ingest — bring your existing instrumentation, drop the second agent.
  • Auto-instrumented deploy markers on every chart, every panel, every alert.
  • Tail sampling by default — keep errors and slow traces, drop the healthy 95%.
  • One query language across logs, metrics, and traces. No DSL hopping.
Book a 30-minute demo
service: api-gateway · p95 latency · last 30m deploy a3f9c2 · 00:09:14
deploy · a3f9c2
p5038ms
p95214ms+62ms
err0.31%
rps4,812
AI incident summarization · in production

The postmortem your on-call would have written at 3am. Already drafted.

Used by 1,800+ on-call teams. Grounded in your logs, traces, deploys, and runbooks. Drafts the executive summary, the timeline, and a defensible root cause before you finish your coffee.

01

Reads the room, not the marketing page.

Summarization runs against the actual incident graph: deploy markers, error spikes, related traces, recent runbook revisions. It cites the artifacts it pulled from — no invented root causes, no hallucinated metric values.

  • Draft lands in the incident channel within ~40s of the page firing
  • Every claim links to the trace / log / deploy it came from
  • On-call keeps final say — drafts are never auto-published
incident #4719 · api-gateway · resolved drafted in 38s

Summary. p95 latency on api-gateway rose from 152ms to 214ms at 00:09:14 UTC, immediately following deploy a3f9c2. Auto-rollback at 00:11:02 restored baseline. No customer-facing impact.

Root cause (likely). New connection-pool sizing in a3f9c2 increased pool warm-up latency. See trace t-9af2 and runbook §pool-sizing.

Timeline.

  • 00:09:14 — deploy a3f9c2 shipped to prod (4 regions)
  • 00:09:21 — p95 alert fires, page routed to @maria
  • 00:10:34 — synthetics confirm regression tied to deploy
  • 00:11:02 — rollback to a3e8b1 · SLO green
02

Trained on your stack, scoped to your tenancy.

Models are fine-tuned against your runbook history and deploy metadata. Customer telemetry is never shared across tenants and is never used for foundation-model training. SOC 2 Type II scoped, with the data-flow diagram in the trust center.

  • Per-tenant model context, isolated at inference
  • Runbooks are read-only inputs — never written back
  • Audit log of every summarization, exportable as JSON
data sourceslogs · traces · deploys · runbooks
scopingper-tenant context
isolationno cross-tenant signal
trainingcustomer data: excluded
outputcited, draft-only, human-approved
03

Closes the loop on every page.

Summarization doesn’t end at the draft. When the incident closes, Yeinz turns the draft into a structured postmortem in your repo, opens the follow-up tickets, and schedules the review — same artifacts your team would have written by hand, in a tenth of the time.

  • Postmortem PR opened against docs/postmortems/
  • Action items become tickets with owners from the participants list
  • Review meeting auto-scheduled with the responding engineers
page fires
draft in 40s
incident resolved
postmortem PR
tickets + review

See the four modules wired into one event graph.

30 minutes. A working session against your real pipeline — bring a repo, leave with a deploy.

Book a 30-minute demo