Kamal Nahas and Anthony Rassi
Kamal Nahas and Anthony Rassi

For most of history, labour has been human. Every task, every job, every dollar earned was the product of human effort. But that's changing as a new class of workers is emerging: AI agents. With the right intelligence and autonomy, these agents can read documents, fill out forms, and get things done. And now? Thanks to Kamal Nahas and Anthony Rassi, they can put money back in your pocket.

Kamal and Anthony are two scientists and entrepreneurs who have dedicated their careers to training and commercialising AI agents that unlock savings for millions of consumers. Their startup PAP! has grown into a $20 million company, recently raising $2.6M from investors like Y Combinator (the accelerator responsible for launching industry giants like Airbnb, Dropbox, and Stripe), General Catalyst (which manages over $32 billion in assets), NFX (known for early investments in breakout companies like Lyft and DoorDash), Bow Capital, and the founder of TrueBill (which was acquired by RocketMoney).

PAP! leverages AI agents to claim money consumers are entitled to but aren't recovering. Every year, billions of dollars in refunds, rebates, and compensations go uncollected — not because people don't want the money, but because the process of getting it is confusing, tedious, and often not worth the hassle. For example, many retailers offer price adjustments if an item goes on sale after you've bought it. But to get that refund, you'd need to dig up receipts, fill out forms, navigate clunky policies, and deal with customer service. Most people don't bother.

But PAP! manages the entire claims process on behalf of consumers from start to finish. Today, its agents are actively working for tens of thousands of users, automatically recovering hundreds of thousands of dollars in cash.

How Two Founders Trained AI to Earn Money Like a Human

While most finance apps help you budget, PAP! was built on a bolder premise: software that could earn money on your behalf. But to do this, you need data to recognise an opportunity and agency to act on it.

Most financial tools use bank statement data as the source of their data. These statements show where you shopped, when you paid, and how much you spent — but not what you bought. You might see a $120 charge from Nike, but that could be a pair of Air Max 90s or a dozen high-quality socks. However, this missing piece of the puzzle would allow an AI agent to determine whether the price drops, if a rebate becomes available, or if the delivery qualifies for compensation — all of which are prime money-making opportunities.

The good news is that this data does exist. The bad news is that it lives buried in your email inbox, hidden inside messy, unstructured receipts and scattered across countless formats, making it impossible to reliably parse this data at scale.

Kamal and Anthony's answer to this problem was a complete reimagining of how email data is extracted and understood. They built PAP!'s AI-powered system from the ground up, designing it to read receipts from any retailer and in any format. With a 98% accuracy, it turns inbox clutter into structured purchase data, unlocking a layer of visibility that traditional finance tools have never been able to access.

When PAP! detects a money-making opportunity, it jumps into action and gets to work on behalf of the user: It chats with customer service, negotiates the refund amount, and follows through until the money lands in your bank account. It's like a personal CFO but better, working around the clock to earn you the money you're entitled to.

Kamal and Anthony's technology is already delivering real results. At the same time, apps like Honey (acquired by PayPal for $4B) might save you a few dollars at checkout, PAP! Earns users an average of $20/month after they buy. To date, it's recovered hundreds of thousands of dollars for users.

From Earning Money to Spending It for You

Kamal and Anthony have since set their sights on a new kind of work: training AI agents to buy things for you.

Until now, most advanced shopping tools only helped you discover products. Platforms like Perplexity Shopping and Daydream might help you find the best carry-on under $200, but you must still compare prices, enter your shipping details, and complete the purchase.

PAP!'s infrastructure aims to take that burden off your hands by not just recommending what to buy but finding the best price, entering your info, and placing the order on your behalf — across any retailer and any checkout flow. It's like handing an AI assistant a credit card and a mission. Just say, "Buy this dress for me," and watch your agent do the work.

That's the future Kamal and Anthony are working to build: the infrastructure for agentic commerce.

The Beginning of the AI Agent Economy

From cash-generating agents to autonomous buyer agents, Kamal and Anthony are creating a new class of digital labour: one that earns, shops and works for you.

To reclaim the money you're already owed, sign up for PAP! for free today. To hear directly from Kamal Nahas and Anthony Rassi as they rewrite the rules of what AI can do for you, follow them on LinkedIn (Kamal, Anthony) and Forbes (Kamal, Anthony).