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Cashew is a minimalist personal finance and budgeting app built with Flutter, designed to help individuals track expenses and income easily. It emphasizes simplicity and clarity, offering straightforward interfaces for adding transactions, categorizing them, and monitoring balances. Users can visualize their financial activity with charts and summaries, giving them insight into spending patterns. Because it is open source, developers can modify or extend it with features like recurring...

Complete and user-friendly retail POS functionality A comprehensive, flexible, and user-friendly cloud-based retail POS software. 1. Sales, quotations, reservations, and returns, including cross-store and cross-channel scenarios. 2. Automatic validation of customer personal data. 3. Configuration of keymaps for quick access to options and featured products. https://www.youtube.com/watch?v=Aai3iYLP2TQ&pp=ygUNb3BlbmJyYXZvIGtkcw%3D%3D Contact: both version of Openbravo POS...

...KEY FEATURES: • Smart Payout Calculator - Automated tier-based revenue splits with self-balancing fairness algorithms • Team Management - Track contributors, assign tiers, manage payment info, export credits lists • History & Reports - Complete payout timeline with statistics, export reports as Markdown or CSV • 15 Comprehensive Guides - Covering team infrastructure, recruiting, marketing, business models, IP law, and collaboration culture Web App: https://rc-revshare-system.reactorcoregames.workers.dev/ Source Code: https://github.com/ReactorcoreGames/Reactorcores-Revshare-System

This is Simple Loan Calculator Script code. You can calculate the monthly payment, the amount of interest paid, the total cost of credit. It is built with JavaScript. Get more free projects : https://mrbroo.com/

Abu Quantitative Integrated AI Big Data System, K-Line Pattern System, Classic Indicator System, Trend Analysis System, Time Series Dimension System, Statistical Probability System, and Traditional Moving Average System conduct in-depth quantitative analysis of investment varieties, completely crossing the user's complex code quantification stage, more suitable for ordinary people to use, towards the era of vectorization 2.0. The above system combines hundreds of seed quantitative models, such as financial time series loss model, deep pattern quality assessment model, long and short pattern combination evaluation model, long pattern stop-loss strategy model, short pattern covering strategy model, big data K-line pattern Historical portfolio fitting model, trading position mentality model, dopamine quantification model, inertial residual resistance support model, long-short swap revenge probability model, strong and weak confrontation model, trend angle change rate model, etc.