YApplied to Y Combinator S26

QA for the AI era.

Teams using AI coding tools ship 98% more PRs. Qlane is your QA co-pilot — real-browser testing on every PR, on-demand sessions, and evidence-grade bug reports.

5 minutes to your first PR test·live demo on request

How qlane fits your codebase

Have a staging or prod URL? Point qlane at it. No build, no provisioning.

eu.qlane.ai/projects/acme/targets/staging
3.2×
Faster QA loop
98%
PRs tested
<2 min
Average PR turnaround
The problem

AI writes the code. Who tests it?

Teams using AI coding tools ship 98% more pull requests — and review time grew 91%. The code volume scaled. The QA didn't.

Without qlane
98%
more PRs merged with AI tools
91%
longer review times
4+ days
average PR wait before review

Source: Faros AI — The AI Productivity Paradox

Qlane is the QA half.
How qlane works

What you actually get on every PR.

Bug reports

Reproducible, not opinionated. Every bug ships with a screenshot, the exact click path, and a severity grounded in user impact. No "looks fine to me" comments.

Test cases

Generated as you ship. Qlane reads each PR diff and drafts the cases that should exist. Drafts only become active tests when a human merges the PR.

Coverage map

What's tested, what's not. Coverage areas mapped to test cases with pass/fail history. Filter by smoke / sanity / regression to see what protects the critical path.

GitHub reviews

Silent on pass. When qlane finds nothing, you hear nothing. Bugs get a structured review with per-bug comments and screenshots. Zero noise on a clean run.

Built for engineering teams

We run your entire application — every service, with realistic data — and an AI QA engineer drives it like a human.

qlane run · pr 247
8.2s
Avg sandbox boot
99.7%
Test determinism
<2 min
PR turnaround
  • Isolated sandbox per PR — no test pollution between runs
  • Real Playwright browser, not headless replay
  • Per-bug screenshots, DOM snapshots, repro steps
  • GitHub review with severity-tagged comments
Capabilities

What the agent does, in every mode.

Whichever runtime you picked above, the agent does the same three things: runs your app, finds the bugs, keeps your suite sharp.

PR Testing

Every pull request, in a real browser.

Every PR runs in an isolated sandbox. The agent navigates your app, finds the bugs that broke, and hands them back as a structured review.

  • Isolated sandbox per PR — no test pollution between runs
  • Agent navigates with Playwright in a real browser
  • Per-bug screenshots, DOM snapshots, reproduction steps
  • GitHub review with severity-tagged comments
  • Silent on pass — no noise when nothing's broken
Whole-App Sandbox

Run your whole stack, not just one service.

Multi-service apps via Docker Compose. The agent runs your stack — every service, with realistic data — and drives it across services to catch integration bugs no single-component test would find.

  • Docker Compose-based runtime — every service running, not stubbed
  • AI writes the Compose file from your repos if you don't have one
  • Realistic data via seed scripts or sanitized DB snapshots
  • Secrets injected from an encrypted vault — never on the sandbox filesystem
  • Auto-pause when idle — you only pay for active compute
Smoke Suite Management

Your critical path stays optimized.

AI proposes promotions, demotions, and archives based on what actually breaks in production. Your smoke suite stays sharp without weekend triage.

  • AI-proposed promotions from regression to smoke
  • Auto-archive cases that haven't found a bug in N runs
  • Coverage gaps surfaced when a new feature ships without tests
  • Three test levels — smoke, sanity, regression
  • Human approval gate — no test enters smoke without sign-off
Under the hood

Built into the agent.

Every qlane run uses the same primitives — the difference between a 5-second smoke and a 5-minute deep investigation is depth, not capability.

Auto test case generation

Every PR diff drafts the cases that should exist. Drafts only become active tests when a human merges the PR.

Coverage Map

Surface areas mapped to test cases with pass/fail history. Filter by smoke / sanity / regression to see what protects the critical path.

Deep testing mode

The agent reads source, instruments code with logs, re-runs, and observes — all inside an ephemeral sandbox that's torn down at session end.

Real-browser evidence

Every bug ships with a screenshot, DOM snapshot, and the exact click path. Repros that survive the round-trip from agent to human.

Multi-trigger

Webhook, GitHub Actions, schedule, manual, push-to-main, deployment-status. Pick what fits your CI; mix as many as you want.

Team access & audit

SSO, project-level roles, audit logs. Secrets stay in an encrypted vault — never in transcripts or logs.

Three ways qlane gets to work

Automated. On-demand. In the wild.

Same agent, three invocation patterns. Pick the one that fits the moment — or use all three.

Automated

On every PR

Webhook fires the moment a PR opens. The agent clones, builds, runs in a real browser, and posts a structured review. No human in the loop until a bug is found.

PR opened → review posted in ~2 min
On-demand

From your team

Your QA team spins up a session whenever they need one — to chase a specific bug, validate a flow on staging, or sanity-check a release candidate. Sessions run from chat in Slack, a Linear ticket, a Jira issue, or the qlane dashboard.

@qlane reproduce ENG-247 on staging
Captured in the wild

Browser extension

See a bug while you're using the app? Click the extension. The agent reproduces it cold, captures evidence, and files a structured report — with the path you took already mapped.

Click extension → bug filed with repro
An AI engineer, not a tool

Qlane is an agent. Reach it where you already work.

Mention qlane in GitHub, Linear, Jira, or Slack. Invoke it from Claude Code or your CI. The agent runs the same evidence-backed tests no matter where you call it from.

GitHub

Mention @qlane on an issue or PR. Assign the bot as a reviewer. Or let the GitHub App test every pull request automatically.

@qlane fix the submit-button bug

Linear

Mention @qlane on an issue or delegate via Agent Sessions. The run threads inline as agent activities — no context-switching between tools.

@qlane verify ENG-247

Jira

Mention @qlane on a ticket. Assignment triggers a session. Findings come back as comments with severity and a deep link to the full run.

@qlane test PROJ-1893

Slack

Run a QA pass from a channel. The agent picks up your project, runs, and reports back in-thread — bugs, screenshots, dashboard link.

/qlane test staging

Claude Code

/qlane:fix loads the bug, repro, and screenshot into your editor. /qlane:test runs a QA pass against localhost before you push.

/qlane:fix PR 247

CI / API

qlane/qa-action@v1 in GitHub Actions, or the REST API for scripting. OAuth and short-lived M2M tokens — no long-lived secrets in your repo.

uses: qlane/qa-action@v1
Built for the whole team

Qlane is a QA co-pilot.

Devs ship faster. QA force-multiplies. PMs see what's tested before sign-off. One agent, three angles.

Enterprise

Secure, compliant, and multi-region.

Your identity provider, your roles, your region. qlane plugs into the controls enterprise teams already run — SSO, SCIM, MFA, and RBAC — with EU/US data residency and encryption built in.

  • and 25+ more SAML/OIDC providers

SSO

SCIM

MFA

RBAC

Audit logs

GDPR

Encryption

Isolated runs

FAQ

Six questions we hear most.

No — they're complementary. Code-review tools like CodeRabbit and Qodo are good at code-level issues: patterns, logic errors, style. Qlane adds the layer they can't — it clones, builds, and runs your app in a real browser, catching runtime bugs, UI regressions, and interaction issues. Teams using both get code-level AND runtime coverage on every PR.
Get started

Three minutes from here to your first PR.