PeakStackBeta
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Private beta · invite only

Ship AI-built software
without shipping the risk

PeakStack connects to GitHub and analyzes every commit, catching security holes, scalability bottlenecks, and runaway cloud costs before they reach production.

We’re onboarding teams gradually. Leave your email and we’ll reach out with an invite.

acme/checkout-api· main
Watching
a3f9c1dadd Stripe checkout endpoint
48716473
7b2e0aacache user profile lookups
86928890
c14d8f2batch order fetch in dashboard
81585269
Reviews the stack you already ship withNext.jsPythonNode.jsPostgresFirebaseStripe

See the analysis up close

Click through the four lenses: real findings, line references, and concrete fixes.

Security
Leaked secrets, injection, broken auth, with the exact line and a fix.
Hardcoded API key committed to sourcecritical
lib/config.ts:14· Fix: Move STRIPE_SECRET_KEY to an env var and rotate the exposed key.
Stripe webhook signature not verifiedhigh
app/api/checkout/route.ts:42· Fix: Verify the `stripe-signature` header with your endpoint secret before trusting the payload.
Rate limiting present on auth endpointpass
app/api/login/route.ts:8

The hidden cost of vibe coding

AI ships features fast, and ships risk just as fast. The numbers from our research:

0%

of AI-generated code contains security vulnerabilities

Wiz · Databricks

0.0%

of AI package suggestions are hallucinated, fueling slopsquatting

arXiv 2501.19012

+0%

rise in vulnerabilities per codebase, now averaging 581.6

Checkmarx

0%

avg. gross margin for scaling AI startups, vs 80%+ for SaaS

GenAI unit economics

Read the full research

Four lenses on every change

Each commit gets scored across the dimensions that actually break products in production.

Security
SQL injection, XSS, leaked secrets, and broken auth, flagged with the exact line and a fix.
Scalability
Static analysis finds the N+1 queries, full scans, and blocking calls that break as you grow 100 → 100k users, with no AI guesswork.
Cost
Estimate cloud and API spend per feature and per user before the bill arrives.
Production
A single launch-readiness score so you know what to fix before every deploy.

And everything around the score

Work Units - code grouped by business capability, so you see where risk actually lives

Ask AI - chat with an engineer that knows your repo, scores, and findings

Architecture - a live map of your system, generated straight from the code

Profitability - turn cost estimates into margin, break-even, and a 12-month projection

Commit + Slack - the digest delivered to the commit and the channel you already watch

Solo or team - invite teammates into a shared workspace whenever you’re ready

One platform vs. a stack of point tools

Today you'd wire together six tools to get part of the picture, and none of them judge production readiness the way an experienced engineer would.

Static analysis
SonarQube
Doesn’t reason about business impact or AI-native risks.
Security
Snyk
Focused on vulnerabilities, not holistic engineering readiness.
Code quality
CodeClimate
Doesn’t understand cloud economics or profitability.
Monitoring
Datadog
Operates after deployment, not before.
Cost management
Cloud cost tools
Reactive: they don’t inspect the architecture before launch.
AI coding assistants
Cursor, Claude Code, GitHub Copilot
Help create software; they don’t independently judge its production readiness.
PeakStack
Pre-deploy coverage across the board
One engineering judgment on every commit, before you deploy - it complements runtime monitoring, it doesn't replace it.

From connect to confident in minutes

No config, no agents to install. Just point it at a repo.

1
Connect GitHub
Authorize access in one click and pick which repos to watch. We read your code; the only write is the optional commit-comment digest, which you control.
2
Push as normal
Every commit is analyzed automatically, with no CI config or agents to install.
3
Ship with proof
Get scored findings and concrete fixes in your dashboard - delivered to the commit and to Slack if you want them where you already work, so you launch knowing it holds up.

Simple, honest pricing

Start free, no credit card. Every repo gets unlimited abridged scans; unlock a repo's full AI report with a scan credit, or subscribe for unlimited full scans and continuous monitoring. Slack delivery is free on every plan.

Free

$0

Abridged scans, plus credits to unlock full reports.

  • 1 repository
  • 5 Work Units
  • Abridged deterministic scan
  • Security findings with fixes
  • 1 free full-report scan
Join waitlist

Starter

$29/mo

Continuous monitoring for indie developers.

  • 5 repositories
  • Unlimited Work Units
  • Everything in Free
  • One-click fixes
  • Ask AI
  • Cost & profitability
  • Scalability simulator
  • Architecture diagrams
  • Launch readiness reports
  • PR comments on every commit
  • Email support
Join waitlist

Recommended

Pro

$79/mo

For growing products and small teams.

  • 20 repositories
  • Everything in Starter
  • Priority support
Join waitlist

Team

$199/mo

Unlimited repositories for teams.

  • Unlimited repositories
  • Everything in Pro
  • Team access
  • Admin console
  • Dedicated support
Join waitlist

Questions, answered straight

What it touches, what it stores, and how the analysis actually works.

It connects to GitHub and reviews your code on every push, scoring four things that actually break products in production (security, scalability, cloud cost, and launch readiness), and returns specific findings with the file, line, and a concrete fix.

Work Units are the heart of how PeakStack reasons about a repo. Instead of judging files or folders in isolation, it groups your code by the business capability it implements (Auth, Checkout, Notifications, and so on), and scores each unit for security, scalability, cost, and readiness. That tells you where risk actually lives ("Checkout is the weak link"), not buried in a flat per-file list. The grouping is AI-proposed but fully yours to curate: create, rename, merge, split, or pin units. Anything you pin is preserved on every re-analysis and re-scored in place, so your curation never gets clobbered.

It reads your code to analyze it and never changes it. The one feature that uses write access is the optional commit-comment digest, and you can turn that off in settings, after which nothing in your repo is ever written. You also choose exactly which repositories it can see, and can revoke access from GitHub at any time.

No. Code is read transiently to analyze it; what we persist is the analysis (scores, findings, file paths, and capability summaries), not your source files. You can disconnect and remove your data whenever you want.

With deterministic static analysis, not AI guesswork. The engine inspects your code for the patterns that fall over under load: N+1 queries, full-table scans, unbounded queries with no pagination, synchronous calls that block the event loop, and quadratic loops. Each one is reported with the exact line and the fix, and feeds a scalability score.

They are projections based on the infrastructure your code appears to use, broken down per capability and per active user. Treat them as directional, good for catching the database or AI call that will dominate your bill, not an exact invoice.

No. There is nothing to install in your pipeline and no config files. Once the GitHub App is connected, every push is analyzed automatically and the results show up in your dashboard.

Yes. Connect Slack in one click and PeakStack posts each digest - the ship score, the top findings, and a link to the full report - to the channel you choose. You decide when it fires: on every analyzed push, or only when there are new findings or the score drops. Slack delivery is free on every plan, including the free tier, and you can mute or disconnect it anytime.

Yes - Ask AI is a chat that knows your repo: its capabilities, scores, findings, and recent commits. Ask why a unit scored the way it did, what to fix first, or how a change affects risk. Free accounts get a few questions a month; subscribers get unlimited.

Both - it’s the same product either way. You get a personal workspace the moment you sign up, and you can create a team workspace and invite teammates by email whenever you’re ready. A workspace owns its repositories, billing, and Slack channel, so the whole team sees the same scores and digests. Solo today, team tomorrow, no migration.

A full first pass over a repository runs in minutes, depending on its size. After that, each push is analyzed incrementally: only the work units touched by the commit are re-scored.

The engineering review works across the stack: common ones include Next.js, Node, Python, Postgres, Firebase, and Stripe. The deterministic scalability checks recognize query, loop, and I/O patterns across JavaScript/TypeScript, Python, Go, Ruby, Java, PHP, C#, and Rust.

Start free, no credit card. Every repo gets unlimited abridged scans - the deterministic checks and a baseline score. To see a repo’s full AI report (the LLM scorecard, line-level findings with fixes, and the cost, scalability, architecture, and launch-readiness modules) you either spend a scan credit on that repo or subscribe. Credits are one-time ($12 for one scan, down to $6/scan in a pack); every new account gets one free. A subscription gives you unlimited full scans plus continuous every-commit monitoring, one-click fixes, and unlimited AI chat. Slack delivery is free on every plan.

Know your code is production-ready before you push

Join the developers shipping AI-built software with confidence.