v1.7.0 — Now available

Your brain
can't stop.
We stop it.

Compulsive scrolling isn't about screen time — it's a loop your brain is stuck in. Pause.ai detects the exact moment you lose control, then physically intervenes. Not a timer. Not a blocker. An interrupt.

94.7% detection accuracy 1.3% false positives 100% offline — zero data sold
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94.7%Accuracy

Integrity Proof: every build is SHA-256 fingerprinted. If a single bit changes, the hash changes. Verify before you install.

9D521D257B6B201BC16FF97E5FA9F00D7F9414A73FDE3F0F93CA0D26121E7EBD
Why Willpower Fails

The Pattern Your Brain Is Stuck In

Screen time apps measure the wrong thing. Your addiction isn't about how long you scroll — it's the reopening loop, the switch spiral, the kinetics. Three signals expose it.

📲
Step 1
Close App

You tell yourself you're done. Close Instagram. Lock phone. You believe it.

🔄
Step 2
Reopen in 2s

Muscle memory. Dopamine withdrawal. You're back before you decided to go back.

Step 3 — We See It
AI Detects Loop

3 reopens in 90 seconds. Context velocity >10/min. Scroll kinetics flagged. Score crosses threshold.

🛑
Step 4 — Interrupted
Physical Block

Full-screen cooldown. Can't dismiss. The loop breaks. Cognitively, that's the moment of reset.

Transparent Logic, No Black Box

Three Signals.
One Compulsion Score.

Each signal is a verifiable behavioral marker backed by HCI research. Tune them. Disable them. We publish the formulas.

01
Reopen Loop

Close an app and reopen it within 2 seconds — three times in 3 minutes. Pure dopamine muscle memory. This pattern does not occur during intentional use. Ever.

threshold: 3× / 90s
02
Context Velocity

10+ app switches in 5 minutes. Your brain is hunting — not working. YouTube → TikTok → Instagram → Telegram in 4 minutes is a compulsion signature, not a workflow.

threshold: 10 switches / 5 min
03
HCI Scroll Model

Scroll velocity × dwell time analyzed through a logistic sigmoid trained on 2,147 sessions. Doomscrolling has a kinetic fingerprint. Intentional reading doesn't match it.

94.7% accuracy / 1.3% FP
Why The Others Don't Work

Discipline Apps
vs.
Compulsion Interruption

Capability Screen Time / Blocker Apps Pause.ai
Detection methodTimer (total minutes)Behavioral signatures (3 signals)
Can you dismiss the block?Yes — one tapNo — physical cooldown enforced
False positive rate50%+ (blocks reading, work)1.3%
Data & privacyCloud synced, sold100% offline, zero collection
Detects reopen loops?NoCore signal
Works when you're motivatedYesYes (tunable sensitivity)
Works when you've relapsed?No — you turn it offYes — cannot be dismissed
Built for the Hard Cases

If You Already Bypass Blockers,
This Is For You.

Any app that lets you dismiss the block in one tap isn't solving the problem — it's just providing friction you're wired to bypass. Pause.ai removes the option.

Willpower is the wrong tool

Compulsive patterns fire before conscious thought. By the time you decide to stop, you've already reopened the app three times. Decision comes after behavior — not before.

We catch the slip, not the session

We don't block you at 45 minutes. We detect the behavioral signature of a compulsion loop 30 seconds into it, then freeze it. The other 95% of your phone usage continues normally.

Math you can verify, not promises

We publish the exact equations driving every trigger on this site. Confusion matrices, precision-recall curves, false positive breakdown. If we're wrong, you can prove it.

Beta Feedback

What Beta Testers Say

★★★★★

"I tried 6 apps before this. Every other one I'd turn off in 20 seconds when the block hit. Pause.ai doesn't give me that option and that's exactly why it works."

Beta Tester — Android 13
★★★★★

"The reopen loop detection is scary accurate. Within the first day it caught 4 cycles I didn't even consciously register. That's the problem — you don't notice you're doing it."

Beta Tester — Android 14
★★★★★

"The 1.3% false positive claim is real. I've been using this for 3 weeks and I can count on one hand how many times it interrupted me while I was actually reading something."

Beta Tester — Android 12
Peer-Reviewed Methodology

94.7% Doomscrolling Detection.
1.3% False Positives on Reading.

Our HCI compulsion model uses velocity, dwell-time, and scroll frequency in a logistic sigmoid validated on 2,147 real user sessions. We publish the equations, thresholds, weights, and validation metrics — all on this site.

Read Science Summary → Read Full Paper →
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