Stash AI
Agentic AI for spending analysis & budget predictions
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Ravi Dubey

Stash AI - Agentic AI for spending analysis & budget predictions

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Stash AI is an agentic finance platform that goes beyond traditional budgeting apps. Its three-layer architecture combines a data layer (transactions, budgets, patterns), an analytics layer (spending velocity, trends, projections), and an LLM layer that turns structured signals into human-readable insights. All calculations run in backend logic, with constrained prompts and validated outputs, enabling proactive financial guidance rather than just retrospective reports

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Ravi Dubey
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Hey Product Hunt! 👋 I built Stash AI out of personal frustration. Every budgeting app I tried told me what I already spent, but none warned me before I overspent. That felt like reading a post-mortem instead of getting a heads-up. So I built the opposite: an agentic financial assistant that catches patterns early and says things like "You're trending 23% over your entertainment budget this month" before the damage is done. This is a demo project, but the architecture is fully functional. The core insight was separating calculation from intelligence. All numerical logic runs deterministically in the backend. GPT-4 Turbo only handles the final translation into human-readable guidance, keeping it accurate and trustworthy, not just conversational. Stash AI delivers four types of intelligence: predictive, behavioral, contextual, and prescriptive. Built with Next.js, MongoDB, and GPT-4 Turbo. Would love your feedback, especially on what financial insights you wish your banking app actually gave you.