Preview

> A peek at what's inside, before it's on the App Store.

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Fast Mode

Pozor busts common myths about how you're actually tracked. Fast mode gives you the short version of each one: what people assume, what's really going on, and one thing you can do about it.

Is My Phone Listening?

Your phone probably isn’t listening. Ads catch up to you through data you already left behind, like search history and shared logins, not your microphone.

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Turn off “Allow Apps to Request to Track.”

Why Ads Follow You Between Apps

Your phone carries a hidden ad ID that lets your activity in one app follow you into another. Turning off tracking permissions shuts that down.

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Turn off “Allow Apps to Request to Track.”

The Coincidence Engine

That eerily fast ad usually comes from a website tracker or a search you forgot about, not real time surveillance.

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Turn off Personalized Ads.

What A Store Actually Learns When You Walk In

Stores use small Bluetooth beacons to sense which aisle you’re standing in if their app is on your phone. Pozor’s scanner shows you the exact same broadcasts.

Try This

Know what your Bluetooth broadcasts.

Companies You’ve Never Heard Of Already Have A File On You

Companies you’ve never heard of buy and trade your purchase and browsing history behind the scenes, building a profile you never agreed to.

Try This

Turn off Personalized Ads.

Location Without GPS

Turning off GPS access for an app doesn’t fully hide your location. Wi-Fi, Bluetooth, and even your cellular connection alone can still place you within a building or a city block.

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Turn off Precise Location for apps that don’t need it.

How Your Devices Get Linked Together

Being logged into the same account on your phone and laptop is often all it takes to link your activity across both, no cookies required.

Try This

Turn off “Allow Apps to Request to Track.”

Dystopian Mode

A completely different, standalone part of the app: cautionary, speculative “where this could lead” scenarios, grounded in real practices already happening today in smaller form. Not a prediction, not a factual claim, a thought experiment about what small privacy habits actually help prevent.

The Claim That Got Denied

Your health plan’s app had a wellness program. You opted in without thinking much about it; it knocked a little off your premium. Years of grocery receipts, a fitness tracker, and a handful of public posts later, an algorithm has quietly scored you as high risk: the skydiving photos, the late-night snack purchases, the gym check-ins that stopped last winter. When you finally need a procedure approved, the score is already in the file. The denial letter doesn’t mention any of it. It doesn’t have to.

The Data Points That Got You Here
  • Grocery loyalty history: what you eat, when, and how much.
  • A fitness app’s activity data, including the gaps in it.
  • Public social posts: hobbies, habits, and risk signals.
  • A wellness program you opted into for a small discount.
Already Happening, In Smaller Form

Insurers already run wellness programs that reward you for sharing health and activity data, and the industry openly experiments with alternative underwriting signals beyond your medical records. The distance from “a discount for sharing” to “a penalty for what it reveals” is shorter than it looks.

Your Price, Just for You

You still book flights on a Tuesday, the old advice everyone half-remembers, a folk ritual for a discount that studies have shown was never reliably real. It was never real because it was never personal: a day-of-week trick assumes everyone gets the same price on the same day. They don’t anymore. Two people open the same checkout page for the same flight, the same jacket, the same insurance quote. They see different numbers. Yours is higher: your phone reads as a newer model, your neighborhood as wealthier, your browsing history as someone who buys rather than shops around. There’s no sale sign, no negotiation, no way to glimpse the other price. The number simply is what a system decided you would tolerate.

The Data Points That Got You Here
  • Your device model and operating system version.
  • Income inferred from your location and neighborhood.
  • Browsing and purchase history: urgency and brand loyalty.
  • The time of day, and how quickly you usually buy.
Already Happening, In Smaller Form

Personalized and dynamic pricing is already documented across travel, retail, and rideshare. Most of it is invisible on purpose: you only ever see your own price, never the one shown to someone else, so the difference is nearly impossible to notice from the inside, the Tuesday myth was comforting precisely because it implied a rule that applied equally to everyone.

Coming soon

Pozor is in development, on its way to the App Store. This preview is a taste, not the whole thing.