In the wake of widespread innovation, a new species of worker is emerging: AI agents that are capable of navigating the web, interpreting data, and taking action. It's a revolution empowered by innovators like Anthony Rassi, an AI and machine learning expert who is crafting these autonomous agents to earn money on behalf of real-world users.
The idea was born when he and his co-founder, Kamal Nahas, realized that billions of dollars are left on the table each year from missed opportunities like post-purchase price drops, unclaimed flight delay compensations, and forgotten class action settlements.
Their solution is PAP!, an AI-powered agent that connects to your email inbox, scans purchase data, extracts financial insights from unstructured data (like receipts and purchase confirmations), automatically files claims to reclaim any eligible savings, and puts money back in your pocket—all without you having to lift a finger.
For Rassi and Nahas, PAP! is part of a wider vision to use agentic AI as a way to maximize savings and optimize digital finances. Let's take a closer look.
Anthony Rassi's Rise in Tech, from Lebanon to USC
At just 15, Anthony Rassi and Kamal Nahas teamed up to build their first solution. At the time, Amazon couldn't ship to Lebanon due to customs regulations, which meant that their peers missed out on trendy products like fidget spinners.
The solution became apparent when Rassi and Nahas noticed a trend of frequent flyers between Lebanon and Paris. The duo realized they could help young shoppers get the products they wanted by creating a machine learning algorithm that connected shoppers with inbound travelers: A user in Lebanon would order a product and ship it to Paris, then the app would help travelers pick up the product and bring the package back to Lebanon on their next trip. The solution went viral, earning Rassi and Nahas five figures in revenue and solving a core user need.
Rassi also won a Lebanese national hackathon by building a platform that helped mid-market and enterprise companies collect user insights at scale. Upon noticing that companies were still relying on in-person questionnaires to gather feedback—a slow, expensive, and inefficient process—he built a full-stack platform that paired users with relevant surveys based on demographic and behavioral signals, leveraging a micro-incentives engine to drive higher response rates.
By connecting brands and consumers for organic, first-party data sharing, this proved to be a faster, more cost-effective, and higher-quality way to gather first-party user feedback data—helping businesses make better decisions while respecting user time and privacy.
Rassi eventually moved to the United States to pursue a dual degree in computer engineering and computer science from the University of Southern California. While there, he served as a course producer for "Introduction to Artificial Intelligence," one of USC's core AI classes, producing technical content while supporting 250 students and guiding them through key ML concepts. He also became an IBM Accelerate Fellow, a prestigious recognition for engineers with great potential.
Simultaneously, he continued to develop his career. One summer, he interned as a web engineer at Lebanon's largest fashion retailer, Aïshti, where he worked on building their e-commerce platform. Next, he joined Addepar (a fintech company that now manages over $7 trillion in assets globally), working as an engineer and developing an algorithm that optimized tax strategies for financial firms and RIAs.
But it was his time at Aïshti that revealed a critical missed opportunity for consumers. There, he noticed how rapidly online prices fluctuated, with a handbag selling for $100 one week and $70 the next. Many retailers offer price adjustment refunds, allowing consumers to reclaim the difference post-purchase—but Rassi realized that almost no one was claiming them. They either didn't know these policies existed, or the claims process was too tedious to bother with.
So after graduating, Rassi reunited with Nahas to start helping online shoppers claim the discounts and refunds they'd been missing out on for so long.
How PAP! Uncovers Hidden Consumer Savings
Most consumers don't have the time or the expertise to unearth the discounts they're entitled to. But thanks to PAP!, they don't need either.
As it turns out, the information needed to identify these discounts lives right in your email inbox—a dormant but powerful gold mine of receipts, purchase confirmations, and class action settlement notifications.
The problem is sorting through and identifying these missed opportunities. While other platforms had tried scraping emails for this information before, they were unable to scale their systems effectively. Every online retailer uses different receipt formats, requiring customized data parsers and precluding the ability to claim universal savings.
So Rassi and Nahas took a different approach. They combined their experience in AI and consumer behavior to build PAP!, an AI-driven platform that's able to parse unstructured data by dynamically identifying the key components of each receipt (like price and product details), regardless of the merchant in question. It also connects the retailer and product information with a search tool to find both the product's updated price and its price adjustment policy. If the price lowers in the time specified in the policy, PAP! automatically requests a refund from the retailer.
"We were able to understand the full scope of consumer spending at a level that has never been unlocked before," Rassi explains. "Our users, to this date, have received refunds from more than 300 merchants, and we expect that number to grow."
For end users, the process is simple: you simply sign up, give access to your email, and let the tool do the work. Instead of an annual fee, PAP! claims a portion of the refund it provides to users. On average, users earn back about $20 per month without needing to lift a finger.
This technology has attracted the attention of many investors, and PAP! is now part of the 2024 Y Combinator cohort, has raised more than $2.6 million from investors like General Catalyst and NFX, and has been valued at $20 million.
Paving the Future of AI-Driven Consumer Finance
Rassi and Nahas' next project is Linda, a pre-purchase optimizer that can find the lowest prices and the best discounts for users. It acts as a personal concierge and only requires users to input the product they want to buy before it searches for the cheapest price point on their behalf. An early MVP test of Linda resulted in an average saving of 19% for consumers.
"In the past, the consumer was forced to control the checkout themselves," says Rassi. "Today, we can control the checkout for our users, applying all possible savings and dynamically checking out on their behalf."
The vision is a future where consumers no longer need to manually track discounts, refunds, or financial optimizations, as PAP!'s AI will handle it for them. By expanding into pre-purchase optimization and automating the entire financial savings process, Rassi sees PAP! becoming the first true AI-powered consumer financial agent, ensuring the best possible prices, claiming any money owed, and making the best deal on behalf of users.
"There are too many ways out there that, if acted upon, could save you money," he concludes. "We want to abstract all of them away from consumers, so they don't have to worry about it while the AI agent always and automatically takes action to implement those savings."
PAP! has proven that any technology designed to simplify savings has incredible potential for success. The next step is building an online shopping infrastructure so these savings can be unlocked every step of the way, from initial product research to long after the purchase is complete, and Anthony Rassi is hard at work to make this vision a reality.
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