Showing 4 open source projects for "document management system using java"

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    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.
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  • Loan management software that makes it easy. Icon
    Loan management software that makes it easy.

    Ideal for lending professionals who are looking for a feature rich loan management system

    Bryt Software is ideal for lending professionals who are looking for a feature rich loan management system that is intuitive and easy to use. We are 100% cloud-based, software as a service. We believe in providing our customers with fair and honest pricing. Our monthly fees are based on your number of users and we have a minimal implementation charge.
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  • 1
    CCruncher

    CCruncher

    Open-Source Project for Credit Risk Modeling

    CCruncher is a project for quantifying portfolio credit risk using the copula approach. It is a framework consisting of two elements: a technical document that explains the theory, and a software program that implements it. CCruncher evaluates the portfolio credit risk by sampling the portfolio loss distribution and computing the Expected Loss (EL), Value at Risk (VaR) and Expected Shortfall (ES) statistics. The portfolio losses are obtained simulating the default times of obligors and...
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  • 2

    openhealthpractice

    A simulation environment for physiology models simulation

    The OpenHealhPractice Simulation Environment is a web framework intended to concurrently manage and launch generalized models. Models can be uploaded by the users and also can be connected to other models in order to simulate them in a row. These simulations are stored and can be reviewed or deleted at anytime. The Graphical Visualization Environment (GVE) provides the graphical visualization of the simulation results. Results can also be exported to different formats (xls, txt or...
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  • 3
    SYSTEM FOR DESIGNING AND SIMULATE CONCURRENT AND DISTRIBUTED PROGRAMS IN CLUSTER ARCHITECTURE Provides graphical interface for configuring relationships between cooperating, abstract processes and simulate it in real cluster environment, using MPI.
    Downloads: 0 This Week
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  • 4

    TOPO

    Simple GUI tool for creating and manipulating WSN topologies

    TOPO is a simple tool that allows the user to create and manipulate arbitrary Wireless Sensor Network (WSN) topologies without worrying about the anomalies that could arise using a text-base topology description. It is fast and easy to use and can accelerate small scale projects such as network simulation. The tool is still undergoing development stage and is open to extension. One the candidate component to be soon integrated is a WSN discrete event simulator.
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  • The full-stack observability platform that protects your dataLayer, tags and conversion data Icon
    The full-stack observability platform that protects your dataLayer, tags and conversion data

    Stop losing revenue to bad data today. and protect your marketing data with Code-Cube.io.

    Code-Cube.io detects issues instantly, alerts you in real time and helps you resolve them fast. No manual QA. No unreliable data. Just data you can trust and act on.
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