Pulsar by Atomically

Your slow pages have a price tag. Pulsar reads it out loud.

Pulsar audits all six Core Web Vitals, runs every metric through a research-backed revenue model, and hands you one number: dollars at risk, with a cited confidence range. It ranks the fixes by ROI, alerts on regressions, and proves the recovery after you ship.

All six vitals: LCP, FCP, CLS, INP, TBT, TTFB
Priced in revenue, not graded out of 100
Cited: Google/SOASTA, Deloitte, Akamai

See how it works

6/6

Core Web Vitals priced in revenue, not just LCP graded out of 100.

Published studies behind every estimate: Google/SOASTA, Deloitte and Akamai.

Low, mid, high

A confidence range on every estimate, never a single figure.

The revenue model

A score of 47 starts an argument. A dollar figure ends it.

Lighthouse hands your engineers a grade. Pulsar hands your CFO a number. The multi-metric model weights all six vitals with page-type multipliers, translates the slowdown into revenue at risk, and attaches a low/mid/high range instead of a single clean lie. Stop arguing about milliseconds. Argue about money.

All six CWV priced, not just LCP
Low, mid, high range on every estimate
Page-type aware: checkout bleeds harder than a blog
Coefficients from Google/SOASTA, Deloitte, Akamai

Monthly revenue at risk

—

LCP—

INP—

CLS—

ROI-ranked fixes

Ranked by dollars recovered per hour of effort. Fix the top one, brag.

A backlog of 40 perf tickets helps nobody. Pulsar sorts every recommendation by ROI: revenue recovered against the effort to ship it. The fix that returns the most for the least work sits at the top, prize and effort already attached. Stop guessing what matters and ship the thing that pays.

Sorted by dollars recovered per hour of effort
Effort sizing on every recommendation
The busywork sinks, the money rises to the top
Track each fix from open to shipped to verified

Top fixes, ranked by ROI

1Defer third-party tagsLow—

2Preload the LCP hero imageLow—

3Code-split the product bundleMed—

Continuous monitoring

The regression that landed at 2am should not wait for the standup.

Pulsar watches your vitals continuously and fires the moment a metric slips. Threshold, trend, competitor, and anomaly alerts, each landing in Slack or a webhook with the dollar cost already attached, so the team triages by money, not by color. Forecasting counts down the days to an SLA breach before it breaks.

Threshold, trend, competitor, and anomaly alerts
Slack and webhook delivery, dollar cost in the message
SLA-breach forecasting with a days-until countdown
Deploy attribution ties the regression to the release

LCP, last 30 days

Regression detected after deploy

Competitor benchmarking

Name your rivals. See exactly where they are faster, priced in revenue.

Name the competitors you actually lose deals to. Pulsar pulls their field data from CrUX and lines it up against yours, vital by vital, then prices the gap. 'They load 1.1s faster on mobile' becomes a revenue line you can take into a planning meeting.

Head-to-head speed bars vs the rivals you name
Real field data via the Chrome UX Report
Faster or slower, shown vital by vital
The speed gap translated into revenue, with alerts

Mobile LCP vs your rivals

You—

rival-a.com—

rival-b.com—

Detect. Price. Fix. Prove. Then do it again.

Most tools stop at the chart. Pulsar runs the whole loop and closes it with proof.

Detect
Continuous Lighthouse and real-user audits on all six vitals catch the regression the moment it lands.
Price
The revenue model turns each regression into dollars at risk, with a cited confidence range.
Fix
Every opportunity ranked by dollars recovered per hour, so the highest-value work is always next.
Prove
Predicted recovery tracked against actual, then rolled into an executive PDF for your boss.

Proof, not promises

We show you the prediction, then we show you what really came back.

Pulsar does not estimate and vanish. It tracks the revenue a fix was predicted to recover against what actually moved after you shipped, so the model is held to reality and your wins are numbers you can defend on a slide. Forecasting counts down to an SLA breach before it happens.

Predicted recovery tracked against actual
Deploy attribution: which release moved the number
SLA-breach forecasting with a days-until countdown
Executive PDF reports for the people who sign budgets

Fix outcome: preload hero image

Predicted

—

Actual

—

Verified after deploy

Built by a Principal Engineer from both venture-backed startups and the Fortune 500.

Dave Quintana built Pulsar from 20-plus years of shipping performance work that moved real revenue. The coefficients come from published research by Google/SOASTA, Deloitte, and Akamai, and we deliberately model the low end. Every estimate carries a confidence range, because honest math beats an impressive lie.

Straight answers, no legal hedging.

How is this different from Lighthouse or PageSpeed?

They hand you a score. Pulsar hands you dollars. Same Core Web Vitals data, run through a revenue model, plus continuous monitoring, ROI-ranked fixes, and proof the fix recovered the revenue.

How accurate are the revenue numbers?

They are grounded in published research (Google/SOASTA, Deloitte, Akamai) and ship with a confidence range, never a single false-precision figure. Import your A/B data and the model calibrates to your real conversion rates.

Do I need to install anything?

No. Pulsar runs Lighthouse from the cloud, so your site does not know it exists. For field data, add an optional 2.3KB (gzipped) RUM beacon: one script tag.

I already use a monitoring or observability tool.

Good, keep it. Those tools show you the metric and the trend. Pulsar adds the layer on top: what the slowdown costs in revenue and the ranked fix to recover it, and it connects to Slack, Jira, Linear, GitHub, and GA4.

Next from the factory: Pulsar.

Coming soon.