Failed Payment Recovery for Subscription Businesses
For subscription companies searching for a failed payment recovery solution to grow revenue, and retain customers.
FlexPay’s innovative platform uses multiple technologies to achieve the highest number of retained customers, resulting in reduced involuntary churn, longer life span after recovery, and higher revenue. Leading brands like LegalZoom, Hooked on Phonics, and ClinicSense trust FlexPay to recover failed payments, reduce churn, and increase customer lifetime value.
Learn More
Turn traffic into pipeline and prospects into customers
For account executives and sales engineers looking for a solution to manage their insights and sales data
Docket is an AI-powered sales enablement platform designed to unify go-to-market (GTM) data through its proprietary Sales Knowledge Lake™ and activate it with intelligent AI agents. The platform helps marketing teams increase pipeline generation by 15% by engaging website visitors in human-like conversations and qualifying leads. For sales teams, Docket improves seller efficiency by 33% by providing instant product knowledge, retrieving collateral, and creating personalized documents. Built for GTM teams, Docket integrates with over 100 tools across the revenue tech stack and offers enterprise-grade security with SOC 2 Type II, GDPR, and ISO 27001 compliance. Customers report improved win rates, shorter sales cycles, and dramatically reduced response times. Docket’s scalable, accurate, and fast AI agents deliver reliable answers with confidence scores, empowering teams to close deals faster.
This project gives a mathematical parser for converting a simple string expression into a result which can be managed for using in other calculations, all in Java.
Using a couple lines of code, you'll be able to parse complex arithmetic expressions efficiently. This library is powered by Dijkstra's Shuting-yard algorithm.
The library has no dependencies with other external libraries.
Dependency
<dependency>
<groupId>com.google.code.mathparser-java</groupId>
...
The fast, flexible, extensible, and easy to use C++ template class for creating your own customized mathexpressionparser for both built-in and user-defined numerical data types. The parsed tree perform fast and can be used in multi-threaded OpenMP apps
Currently, this project consists of a pure java mathexpressionparser optimized for repeated evaluation. Development of an interactive 3D math visualization application based on this parser is planned for the future.