Your infrastructure copilot
Skippy

Meet Skippy

An AI copilot in Slack that monitors your infra and brings you the context — so you do less.

Connects to your entire stack. Runs on-prem. Zero telemetry from day one.

Connected
GitHub
GitHub
3 clusters
Kubernetes
Kubernetes
12 dashboards
Grafana
Grafana
2 teams
Linear
Linear
3 actions taken today

Opened PR for api-gateway overcommit · Flagged slow query on orders · Caught billing spike in us-west-2

Custom solutions running

What people are saying

Straight from Slack

Helped us debug a pod restart issues on day 1

Aash Jain
Aash Jain

Founder at Sample

grinding through a misconfig and almost forgot to update one of the deployments; having Skippy periodically recheck the incident was a lifesaver!

Henrik Laxhuber
Henrik Laxhuber

Founder at Rome AI

Did skippy really do it and make no mistakes?

Tanner Scadden
Tanner Scadden

Founding Engineer at Vitalize

bot is insane

Lou Jug
Lou Jug

Product Lead

An alert fires. Skippy's already on it.

The moment something pages, Skippy pulls the metrics, logs, and recent deploys, tells you exactly what's wrong, and acts — restart, roll back, scale, page the right person. When it's just noise, it says so and moves on.

#incidents
SkippySkippy is responding
Acts on your termsRestartRoll backScalePage on-callDismiss noise

Assign it. Walk away.

Hand Skippy a watch — for the next 30 minutes or the next 10 hours. It checks on a schedule, stays quiet while things are healthy, and gets loud the moment something breaks.

#prod-alerts
SkippySkippy is on watch
Also great forValidate a fix over 10 hoursWatch a deploy roll outRecurring metric queriesOn-call backup

One MCP URL. Your whole stack, any client.

Expose Skippy as an MCP server — one URL you share with the whole team. Drop it into any MCP client — Claude Code, Cursor, and more — and you instantly have CloudWatch, SigNoz, kubectl, Grafana, all wired in. Set it up once; everyone debugs with full prod context.

mcp.json
SkippySkippy MCP

One URL · shared with your team

{
"skippy": {
"url": "https://skippy.yourco.internal/mcp"
}
}
1 connection · 5 tools live
CloudWatchCloudWatchSigNozSigNozkubectlkubectlGrafanaGrafanaGitHubGitHub
si

why are checkout pods restarting in prod?

Skippy

Checked kubectl, CloudWatch & SigNoz — OOMKilled on checkout-api, memory ceiling hit right after deploy #482.

Why teams love itOne URL to shareWorks in any MCP clientReal prod context100× faster debugging
Full-stack context

Deeply integrated. Sees your entire stack.

Connect your tools and Skippy builds one complete picture — what you run, who owns it, and how your team works — so every alert it handles and every watch it runs is grounded in real context.

Skippy
GitHub

GitHub

Sees your entire stack

GitHub, Kubernetes, Grafana, PlanetScale, AWS, Slack — connected into one complete picture.

Knows your team

Learns who owns what, your runbooks, and who’s on-call — so it calls out the right person by name.

Bespoke to your org

Every team is different. Skippy builds custom solutions specific to how your team actually works.

Always Learning

Skippy remembers

Every review, every merge, every rejection teaches Skippy something new. It builds a memory of your infrastructure and your preferences — getting sharper with every interaction.

Skippy Memory
Skippy

Pattern recognized

You always set resource requests to 2x the P95 usage. Skippy now does this by default.

Learned from 12 merged PRs
Long-term memory
Privacy First

Your data stays yours

Privacy isn't a feature we added later. It's how we built Skippy from the ground up.

On-prem by default · Air-gapped or hybrid · Telemetry off by default
Your Infrastructure
Your Network
Kubernetes

K8s Cluster

prod-east

Grafana

Grafana

Internal

GitHub

GitHub

Enterprise

S

Skippy runs here

Inside your network. Inside your control.

Secured
X

No data leaves your network · No analytics · No tracking · No telemetry endpoints

Air-gapped deployment shown. Hybrid setups offload only inference to a managed LLM — everything else stays in your network.

On-prem by default

Every Skippy deployment runs inside your own infrastructure — designed to run on-prem on AWS. Never multi-tenant, never our cloud.

Air-gapped or hybrid

Run Skippy fully air-gapped with zero outbound traffic, or go hybrid and offload only inference to a managed LLM to cut compute cost. Your call, per environment.

Telemetry off by default

No usage data, analytics, or phone-home — off by default. In compliance-sensitive environments, zero telemetry, period.

Your keys, your control

Bring your own LLM API keys. Your credentials are encrypted locally and never transmitted. Full audit trail on every action.

Desktop App

Meet Sailor

Not a new dashboard. Sailor unifies the monitoring dashboards you already run — Datadog, Grafana, SigNoz — and renders them inline, in context with the AWS & GCP resources they're watching.

DatadogDatadog
GrafanaGrafana
SigNozSigNoz
in context with your AWS & GCP objects
Sailor
GrafanaGrafanaEmbedded · live
CPU usage · production-clusterlast 6h

production-cluster

us-east-1 · v1.29 · 4 nodes

Active
41%
CPU
39%
Memory
52%
Pods
NodeEst. Cost
ip-10-0-1-42
t3.xlarge
$2.47
ip-10-0-2-18
m5.large
$1.84
ip-10-0-3-91
c5.xlarge
$3.12
ip-10-0-1-67Cordoned
t3.medium
$0.62

We've helped teams build & ship at

From infra consulting to custom tooling — we work with teams to solve hard problems.

Sample HealthcareVitalizeRome AI

We're slowly rolling out access

We'd love to talk!

Get access

On-prem deployment · Zero telemetry · macOS & Linux