Losing personal items can be incredibly frustrating, especially when they are merely left behind in places like airports or sports stadiums, making retrieval difficult. My friend Caitlin is experiencing this firsthand; she’s yet to recover her phone lost at Oktoberfest on September 27, even after receiving confirmation in November that it was found.
While Oktoberfest is an extreme case, many items are left behind in various settings, including hotels, transportation, and events. For instance, the MTA transit system in New York reported over 18,000 lost items between 2018 and 2023—this figure includes the pandemic shelter-in-place period. That’s where Boomerang believes AI can make a significant difference in lost and found solutions.
This Miami-based startup has developed software that leverages machine learning to connect photos and descriptions of lost items. Clients—from gyms to theme parks—can upload images and details of items they've found, while users can describe what they've lost. If a match occurs, users can either pick up their items or have them shipped directly.
Boomerang aims to streamline the retrieval process for consumers, replacing the outdated method of repeatedly calling customer service for updates, according to co-founder and CEO Skyler Logsdon.
The company's inspiration stemmed from a trip to Cabo, as Logsdon shared. During the journey, his friend Philip Inghelbrecht—a former co-founder of Shazam—lamented about the constant loss of items by his young daughters. The situation became even more pressing when Inghelbrecht’s fiancée misplaced her ring at the Cabo airport.
This prompted Logsdon and Inghelbrecht to create Boomerang, employing a matching concept akin to Shazam. Logsdon emphasized the importance of accuracy in their algorithm: it must make precise matches, just as Shazam identifies a single correct song from a melody.
“Accuracy is key. If Shazam could only say it might be one of ten songs, it wouldn’t serve its purpose,” Logsdon noted. “Shazam delivers the exact song, not an approximation.”
Boomerang recently secured a $4.9 million seed round, led by LightShed Ventures with contributions from GGV, SeventySix Capital, and notable angel investors like Drake and NFL player Christian Kirk. Logsdon mentioned that this funding will help onboard new partnerships. The startup is already collaborating with various organizations, including State Farm Arena, home to the Atlanta Hawks, and Universal Studios Hollywood.
While it’s clear why consumers would appreciate a more efficient lost and found system, I initially questioned why organizations—who pay for the software—would be motivated to participate. After all, would a negative experience with a venue’s lost and found deter someone from attending their favorite team’s game at the stadium again?
Logsdon explained that enhancing this aspect can significantly boost customer satisfaction. However, many venues face a logistical nightmare with lost and found items, more than I realized. Some locations amass thousands of items after each event, leaving their customer service teams overwhelmed with constant inquiries.
Additionally, Boomerang collaborates with hotels and airports, where items of considerable value—like laptops, medical devices, or even power tools—are often left behind, rather than just trivial items like a $20 water bottle or a cap.
Boomerang represents an innovative application of machine learning and AI in a traditional industry. While much of AI advancements focus on speeding up digital processes, Boomerang aims to automate the cumbersome phone and email systems that currently dominate lost and found efforts. Though human involvement is necessary for uploading items, the platform significantly reduces the workload of sifting through countless calls and emails.
Maybe Boomerang could even facilitate the retrieval of lost items from Oktoberfest.
“Boomerang addresses a significant problem that resonates with many," Logsdon expressed. "Everyone has misplaced something at some point. It raises the question: why doesn’t technology already provide a better solution than endless phone calls?”
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