Detect. Alert. Fix.
In minutes, not days.
AuditJet runs continuous synthetic tests against your site, correlates performance drops with revenue impact, and generates code-level fixes automatically.
01
Map your site
AuditJet discovers all the URLs that matter — product pages, checkout, landing pages. Each one gets its own monitoring profile with per-page score thresholds.
auditjet.co / — site map
02
Run against the real web
Every scan simulates a real user on mobile with 4G throttling — because that's who's actually visiting your site. Powered by Google's Lighthouse engine, the same infrastructure behind Google's own performance standards.
Scanning: shop.example.com
Scan complete · 14.2s
03
Connect speed to revenue
Our AI Revenue Agent maps every performance metric to its conversion impact. A 1s LCP regression isn't just a score drop — it's an estimated $175/hr leak on your checkout page.
Regression detected
/checkout · LCP 1.3s → 4.2s
The complete loop
Frequently asked questions about how AuditJet works
How long does the first AuditJet audit take to complete?
AuditJet queues your initial scan the moment you add a URL. For most sites the first Lighthouse report is ready within 60 seconds. The scan simulates a mobile user on a 4G connection, so the engine accounts for network throttling, CPU slowdown, and real-world asset loading before producing your LCP, INP, CLS, TTFB, and FCP readings.
What happens after AuditJet detects a performance regression?
When a monitored metric crosses a threshold you configured, AuditJet triggers an alert immediately via Slack, email, or webhook — whichever channels your team has connected. Alongside the alert, AuditJet generates an AI fix blueprint that pinpoints the root cause at the code level and suggests specific changes, so engineers can act without spending time reproducing the issue.
Can I customize which pages AuditJet monitors?
Yes. After AuditJet maps your site you can select any subset of pages for continuous monitoring and set independent pass/fail thresholds on each one. A checkout page might warrant a 2.0s LCP ceiling while a blog post tolerates 3.0s. Per-page threshold configuration means alerts surface only when the pages that matter most to your business regress.
How accurate is AuditJet's revenue impact estimate?
AuditJet's revenue model applies industry conversion-rate research to your specific metric deltas. The estimate is a directional signal — it translates a performance regression into an approximate hourly dollar figure based on your traffic tier — rather than an accounting-grade guarantee. Teams use it to prioritize fixes by business cost rather than raw score, which surfaces the highest-ROI optimizations first.
Does AuditJet work with any website, or only specific frameworks?
AuditJet monitors any publicly reachable URL regardless of the technology stack. Whether your site runs on Next.js, WordPress, Shopify, a custom Ruby on Rails build, or a static site generator, AuditJet's scanner measures the page as a browser would see it. There is no SDK to install for synthetic monitoring — simply add your URL and scanning begins automatically.
What is an AI fix blueprint and how specific is the fix guidance?
An AI fix blueprint is a code-level remediation plan generated by AuditJet when a regression is detected. Instead of generic advice like "reduce image size," the blueprint identifies the exact asset, DOM element, or script responsible and provides a concrete implementation suggestion — for example, adding fetchpriority='high' to a specific LCP image or splitting a long JavaScript task in a named file. The specificity depends on the information available in the Lighthouse trace, but most blueprints include file-level or selector-level guidance.
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