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Moliyachi

Your AI-powered personal finance assistant inside Agrobank Mobile

The Problem

A significant number of Agrobank's customers live on a strict salary cycle, facing stress and uncertainty every month

Aggressive spending after salary arrival
Mid-month financial stress & uncertainty
No visibility into spending behavior
Lack of personalized budgeting guidance
Current banking apps provide transactions, not intelligence
Users need a way to understand their financial behavior—not just view their balance

The Solution

Meet Moliyachi

A smart financial assistant fully embedded into AgrobankMobile that transforms it from a transaction tool into a financial partner

AI Spending Insights

Short, actionable explanations of where your money goes

Smart Monthly Planning

Warnings when spending is too fast & balance predictions

Financial Health Score

One simple score (0–100) explaining your stability

Goal Planning

AI calculates timelines and suggests improvements

Personalized Recommendations

Based on spending patterns, habits, income, and goals

Agrobank Product Matching

AI suggests Microloans, Deposits, Savings, and Installment options

AI Shop Agent

Find the perfect product with AI-powered recommendations. Get installment options via Opencard by Agrobank, price comparisons, and personalized insights.

Why Our Team?

We are not just building features — we are building a financial intelligence layer for Agrobank

We move extremely fast

All members are Lead and Senior level engineers capable of shipping an MVP within days

We know the problem

Most of us live on a salary cycle and personally experience the challenges we are solving

Strong technical background

We cover ML/AI, Backend, Fintech logic, and Modern UI/UX

Roadmap

Development Plan

Stage 1: Demo Website

Nov 26 – Nov 30

Landing website
Problem & Solution
Architecture planning
Initial AI insights
Everything written from scratch
Frontend development of demo MVP started
Currently has UI template, development in progress
Basic CI/CD, environment setup, base deployments

Functional MVP Shell

Dec 1 – Dec 5

Next.js frontend base
Visual dashboard layout
Mock profile setup
Frontend-Backend pipeline

Core MVP Functionality

Dec 5 – Dec 10

AI recommendation engine
Goal calculator
Financial Health Score
Salary-cycle warning

Polish & Submission

Dec 10 – Dec 13

Supabase integration
LangChain pipeline
Final UI polishing
Deployment (Vercel/Render)

How We Plan to Solve It

We build a thin, intelligent AI layer on top of Agrobank's financial infrastructure

Key Implementation Steps

Collect structured data: salary, age, family size, occupation, financial goals, currency preferences
Extract static data: income streams, spending history, recurring payments, loans, assets, liabilities (NOTE: For hackathon purposes static mock data close to real life data is used)
Normalize & store in secure DB (PII-safe)