SIMP

• Who is the user? Urban gig workers in India—particularly food-delivery riders and ride-hailing drivers—whose income changes significantly from week to week while essential expenses like rent, food, fuel, and EMIs remain relatively fixed. • What exactly is their pain point? – Their biggest problem isn't necessarily low income—it is unpredictable income. A worker may earn enough on average but suddenly face a bad week because of rain, reduced demand, fewer working hours, festivals, traffic, or other disruptions. They often realize they have a cash-flow problem only after the income shortfall has already happened. • What will your product do? KAMAI.AI predicts a worker's income for the next 7–14 days, identifies the likelihood and size of an upcoming income shortfall, explains why it is expected, and calculates how much financial buffer they would need to absorb it. Instead of reacting after a financial crisis, the worker gets an early warning and can take preventive action. It will also tell them how to solve this issue. • What makes your solution different? Most fintech products are designed to lend money after someone needs it or assess whether someone is creditworthy. We do something fundamentally different: we try to predict the financial shock before it happens. We combine the worker's historical earnings and working patterns with external signals such as weather, demand patterns, day of the week, holidays, and local conditions to create a personalized "financial weather forecast." So instead of: “You don't have enough money. Here's a loan.” we ask: “Your income is likely to fall next week. Here's why, here's how large the gap could be, and here's the buffer you need.”

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• javascript
• python