Flyback.ai

Flyback.ai is the first buy-side intelligence platform purpose-built for the luxury watch market. It transforms how collectors, enthusiasts, and investors discover and evaluate deals by replacing guesswork with data-driven certainty. The platform aggregates live listings from over 20 global sources including eBay, Chrono24, Jomashop, Watchfinder, DavidSW, Subdial, and Yahoo Auctions Japan, then applies proprietary machine learning models to score every single deal in real time. Unlike traditional price trackers that rely on noisy asking prices, Flyback trains its models exclusively on hundreds of thousands of verified sold transactions. This fundamental distinction means you see what watches actually trade for, not what sellers hope to get. Every listing receives a 0 to 100 deal score that factors in comparable sales data, seller reputation, condition, completeness of set, and current market velocity. The platform also provides fair value forecasts with confidence ranges, historical price trends by reference, and a market trends dashboard tracking average sold prices and volume shifts across brands and segments. Flyback is free to use and designed for anyone from first-time buyers to seasoned collectors who want to stop overpaying and start finding genuine value. Whether you are hunting for a specific reference or exploring opportunities across brands, Flyback empowers you to buy with confidence, not hope.

Real-Time Deal Scoring Across 20+ Sources

Every listing aggregated from marketplaces like eBay, Chrono24, Watchfinder, Bob's Watches, Bezel, Jomashop, DavidSW, Timepeaks, Subdial, and more is analyzed and given a 0 to 100 deal score. This score is not a simple price comparison. It is a multidimensional evaluation that weighs the listing price against comparable sold transactions, the seller's reputation score, the watch's condition grade, whether it includes box and papers, and the speed at which similar references are moving in the market. A score of 100 means an exceptional deal, while a score below 50 signals you should keep looking. This feature transforms a chaotic sea of listings into a clear, actionable priority list.

Fair Value Forecasts with Confidence Ranges

For qualifying listings, Flyback's machine learning model estimates a fair market value adjusted for condition, box and papers, and seller history. These forecasts are trained on thousands of real transactions, not asking prices. The model outputs a fair value range with a confidence percentage, so you know how much room there is for negotiation or how much you are saving compared to the market. This feature eliminates the anxiety of wondering if you are paying too much and gives you the data you need to make a confident offer or pull the trigger on a purchase.

Personalized Wrist Fit Analysis

Enter your wrist circumference and Flyback recalibrates its entire deal scoring system based on lug-to-lug fit. The platform covers over 2,300 watch references across 32 brands with 100% lug-to-lug measurement coverage. It also adjusts for lug curvature type including straight, curved, or integrated lugs. No more buying watches that look perfect online but wear poorly on your wrist. This feature filters out deals that simply will not fit you, saving you time, money, and the disappointment of a return. It turns the shopping experience from a gamble into a precise, personalized search.

Market Trends Dashboard

Track average sold prices and volume shifts across brands, segments, and specific references over time. The dashboard provides historical price trends that reveal whether a model is appreciating, depreciating, or holding steady. You can also monitor market velocity, which shows how quickly certain references are selling. This intelligence helps you time your purchases and spot emerging opportunities before the broader market catches on. Instead of relying on anecdotal forum chatter or social media hype, you get hard data on where the market is actually moving.

Finding Undervalged Listings Before They Disappear

A collector looking for a specific Rolex Submariner reference can use Flyback to scan 20+ marketplaces simultaneously. The AI identifies listings priced significantly below comparable sold transactions and flags them with a high deal score. Instead of manually refreshing multiple tabs and hoping to spot a bargain, the collector receives a prioritized feed of genuine deals. They can act fast with confidence, knowing the score is backed by real sales data. This turns the hunt from a frustrating chore into an efficient, rewarding process.

Evaluating a Seller's Asking Price During Negotiations

A buyer finds a pre-owned Omega Speedmaster on Chrono24 but the price feels high. Instead of guessing, they paste the listing into Flyback or search the reference. The platform shows the fair value estimate based on recent sold transactions of the same reference in similar condition. The buyer now has a data-backed target price for negotiation. They can message the seller with confidence, knowing exactly what the market supports. This shifts the power dynamic from the seller's optimism to the buyer's intelligence.

Building a Diversified Watch Portfolio with Data

An investor wants to allocate capital into pre-owned luxury watches but needs to avoid overpaying. They use Flyback's market trends dashboard to identify brands and references with strong price appreciation and healthy volume. They then scan listings for those references using deal scores to find entry points below fair value. Over time, they track their portfolio's performance against historical price trends. Flyback replaces emotional buying with a systematic, data-driven investment strategy that minimizes downside risk.

Ensuring a Watch Will Fit Before Buying

A buyer with a 6.5-inch wrist is considering a Panerai Luminor known for its large case size. Instead of relying on wrist shots from influencers, they enter their wrist circumference into Flyback's wrist fit tool. The platform checks the lug-to-lug measurement and lug curvature of the specific reference and confirms it will wear well. The buyer can now confidently purchase knowing the watch will look and feel right. This eliminates the most common regret in watch buying and makes the online shopping experience as reliable as trying on in person.

How does Flyback determine the deal score for a listing?

The deal score is a 0 to 100 rating calculated by comparing the listing price against a machine learning model trained exclusively on verified sold transactions of the same reference. The model also factors in the seller's reputation score, the watch's condition grade, whether it includes box and papers, and the current market velocity for that reference. A higher score means the listing is priced below what comparable watches have actually sold for, making it a genuine deal. The score updates in real time as new listings and sales data are aggregated.

Is Flyback free to use and what sources does it monitor?

Yes, Flyback is completely free to use with no subscription or hidden fees. The platform currently aggregates listings from over 20 global sources including eBay, Chrono24, Watchfinder, Bob's Watches, WatchMaxx, Bezel, Jomashop, DavidSW, Timepeaks, Yahoo Auctions Japan, Subdial, The 1916 Company, Tourneau CPO, European Watch, AuthenticWatches, Birmingham Luxury Watches, and Jared. The list of sources is continuously expanding to provide the most comprehensive coverage of the secondary market.

How does the wrist fit tool work and what data does it use?

You enter your wrist circumference into the tool, and Flyback recalibrates its deal scoring based on lug-to-lug fit for each watch reference. The platform covers over 2,300 references across 32 brands with 100% lug-to-lug measurement coverage. It also accounts for lug curvature type including straight, curved, or integrated lugs. This means a watch that is technically within your wrist size range but has a straight lug that overhangs will be flagged as a poor fit. The tool ensures you only see deals for watches that will actually wear well on your wrist.

What is the difference between fair value estimates and asking prices?

Fair value estimates are generated by Flyback's machine learning models trained on thousands of verified sold transactions. They represent what comparable watches in similar condition have actually traded for, not what sellers hope to get. Asking prices are often inflated by seller optimism or market noise. By focusing on sold data, Flyback provides an objective anchor for what a watch is truly worth. This distinction is critical because a watch listed at $8,000 means nothing without knowing that comparable pieces sold for $6,200 last month.