The only AI built for consumer finance - it has listened to over a billion lending and collections conversations, so your agents don't have to wing it.
Somewhere right now a borrower's phone is ringing. On the other end, instead of a tired agent fumbling through a compliance script and a stack of sticky notes, there is a system that has already heard this exact conversation a million times before. It knows what to say, when to soften, and exactly which sentence a regulator would frown at. That system is Prodigal - and it is quietly rewiring one of the least glamorous corners of finance.
Consumer lending and collections is an industry built on awkward phone calls and paperwork nobody enjoys. For decades the data inside those calls - the hesitations, the promises to pay, the small print read aloud - simply evaporated the moment the line went dead. Prodigal's bet, placed back in 2018 by three IIT Bombay graduates, was that those conversations were the most valuable asset in finance, and everyone was throwing them away.
The company didn't start with a flashy chatbot. It started by listening. By 2019 it had analyzed 200 million interactions and found product-market fit - not by guessing what lenders needed, but by hearing it. That data became a moat, and the moat became a platform.
Everything connects through PIE, the Prodigal Intelligence Engine - the layer that remembers context so the agent (human or AI) never starts cold.
An AI agent that services and collects 24/7 across voice and digital, running operations end to end.
The intelligence engine trained on 1B+ interactions that carries context between every application.
Omnichannel platform that runs digital collections strategy across every channel.
Propensity-to-pay and intent scoring powered by interactions and 500+ consumer attributes.
An AI-native self-serve payment portal that lifts how many consumers pay on their own.
Automated, standardized call notes written in real time - now available in Spanish.
Real-time agent assistance with dynamic prompts during live conversations.
QA automation, scorecards and revenue insights pulled straight from interaction analytics.
Prodigal reports these as upper-bound results across deployments - directional, not guaranteed.
All three met at IIT Bombay before landing in Mountain View. Gangal frames the work as building intelligence that acts "with human-like precision"; Raje runs an engineering culture he describes as rooted in empathy and real-world problem-solving. The company's five values - curious optimism, pursue excellence, bias for action, radical candor, and specificity - read less like a poster and more like a code review checklist.
Return to the borrower whose phone was ringing at the start. The call still happens - people still owe money, and money is still uncomfortable to talk about. But the conversation is different now. The script writes itself, the compliance line never gets skipped, the notes are typed before anyone hangs up, and the next person to call already knows what was said. Prodigal didn't make debt collection glamorous. It made it remember. And in an industry that spent decades letting its most valuable conversations vanish into dial tone, remembering turns out to be the whole game.