Search results for Jobware

Shoviv SharePoint Migration tool is a robust and reliable solution designed to simplify the migration process. The application allows users to migrate between all versions of SharePoint, including both On-Premises and Online environments. With this application, users can migrate data from SharePoint to Google Drive, Google Shared Drive, and OneDrive. It runs job-based, process allowing to runs the multiple jobs at a time. It enables the seamless migration of Sites (classic and modern), Site Collections, MS Teams Sites, Office 365 Group Sites, Document Libraries, and more.

Shoviv Yandex Disk Migrator is an advanced solution designed to provide reliable and hassle-free data migration. It supports migration from Yandex Disk to multiple cloud platforms, including Google Drive, Google Shared Drive, Microsoft OneDrive, Dropbox, Box, Microsoft SharePoint, Amazon S3, and other S3-compatible storage services. The utility operates on a job-based processing system, allowing users to run multiple migration jobs simultaneously with high speed and efficiency. It also offers a wide range of user-centric features, a user-friendly interface, and 24/7 technical support to ensure a smooth migration experience.

Kraaft is a field communication and coordination platform designed for construction, infrastructure, and service teams. Instead of relying on scattered WhatsApp threads, emails, or phone calls, crews share real-time updates, photos, tasks, and reports directly from the jobsite. Kraaft turns day-to-day messaging into structured project data—giving managers clear visibility into progress, documentation, and issues as they happen. With job-based chats, GPS visibility, automatic reporting, and an intuitive mobile app, Kraaft helps field and office teams stay aligned, reduce delays, and deliver consistent, high-quality work across every project.

Shoviv G Suite to Office 365 Migration is an efficient way to migrate Google Workspace to a Microsoft 365 mailbox. It runs on a job-based process, and it can run multiple jobs in a single process. This software has a simple GUI and requires a few easy steps to migrate. Users can apply date and folder-based filters to migrate only specific data. Its incremental export feature enables users to resume interrupted processes and prevents duplicate item migration. The tool also allows setting a limit for failed items to control migration outcomes. Additionally, it supports Google Drive to OneDrive migration. A demo version of the application is available on Shoviv Software's official website, which allows users to process the first 50 items per folder for free.

Shoviv Office 365 Backup Tool is an advanced solution designed to back up and export mailboxes from Microsoft Office 365 to PST format. Built with a highly advanced algorithm, the software offers a range of powerful features to ensure efficient and reliable data management. It allows users to export Office 365 mailboxes to PST files with just a few clicks. The tool also supports incremental export, ensuring that only new or modified data is processed in subsequent operations. Additionally, it is capable of importing PST file data back into Office 365. The software operates on a job-based processing system, enabling users to create and run multiple jobs concurrently. It is compatible with all Windows operating systems, providing flexibility and ease of use.

Shoviv Google Workspace Migration Tool is a professional solution to migrate Google Workspace to Google Workspace. It transfers emails, attachments, and folder structures while preserving complete data integrity, with no limitations on mailbox size or count. The tool supports bulk migration of multiple accounts simultaneously, CSV-based mailbox mapping for large-scale jobs, and delta (incremental) migration to resume interrupted transfers and prevent duplicate data. Users can apply advanced filters by date and folder, automate migrations with a built-in scheduler, and review detailed HTML reports after completion. With its simple, job-based interface, the tool works well for both technical admins and non-technical users. A free demo version is available to migrate the first 50 items per folder before purchase.

The PyTorch 0.3 Python 2.7 CPU Notebook is a pre-configured and fully integrated runtime environment designed for machine learning and data science applications. It combines PyTorch 0.3, an open-source machine learning library, with Python 2.7 and Jupyter Notebook, a browser-based interactive platform for programming and data analysis. This stack is optimized for CPU performance, providing a stable and tested execution environment suitable for both short and long-running high-performance tasks. It can be seamlessly integrated into continuous integration and deployment workflows, making it ideal for training, inference, or running as an API service. Key Features and Functionality: - Integrated Software Stack: Combines PyTorch 0.3, Python 2.7, and Jupyter Notebook for a cohesive development environment. - CPU Optimization: Tailored for high-performance tasks on CPU, ensuring efficient resource utilization. - Versatile Deployment Options: Can be installed on new or existing Linux servers, run as a virtual machine, used as a base image for Docker or Vagrant, or launched on various cloud platforms. - Development Tools: Includes a development preset with essential tools like C compiler and make for program development and building. Primary Value and User Solutions: This product addresses the need for a ready-to-use, stable, and high-performance environment for machine learning and data science projects. By integrating essential tools and libraries, it reduces setup time and complexity, allowing users to focus on development and research. Its CPU optimization ensures efficient execution of tasks without the need for specialized hardware, making it accessible for a wide range of users and applications.

The AISE PyTorch 0.4 Python 2.7 CPU Notebook is a pre-configured and fully integrated software stack designed for machine learning and data science applications. It combines PyTorch 0.4, an open-source machine learning library, with Python 2.7 and Jupyter Notebook, a browser-based interactive environment for programming and data analysis. This setup is optimized for CPU performance, providing a stable and production-ready environment for both short and long-running high-performance tasks. Key Features and Functionality: - Integrated Environment: Combines PyTorch 0.4, Python 2.7, and Jupyter Notebook in a single, ready-to-use package. - CPU Optimization: Tailored for high-performance execution on CPU architectures, ensuring efficient training and inference processes. - Development Tools: Includes essential development tools such as a C compiler and build utilities, facilitating program development and customization. - Stability and Support: Offers a stable, production-ready environment with long-term support and regular updates to maintain reliability. Primary Value and User Solutions: This product addresses the need for a streamlined and efficient setup for machine learning practitioners and data scientists who prefer or require a CPU-based environment. By providing a pre-configured stack, it eliminates the complexities associated with manual installation and configuration of individual components. Users can focus on developing and deploying machine learning models without the overhead of environment setup, thereby accelerating project timelines and enhancing productivity.

The LEMP Stack PHP 7 on Ubuntu is a pre-configured Amazon Machine Image (AMI) designed to streamline the deployment of web applications on AWS. This stack integrates Linux (Ubuntu, Nginx, MySQL, and PHP 7, providing a robust and efficient environment for developers and system administrators. By offering a ready-to-use configuration, it eliminates the complexities associated with manual setup, allowing users to focus on application development and deployment. Key Features and Functionality: - Pre-Configured Environment: The AMI comes with Nginx, MySQL, and PHP 7 installed and configured, reducing the time and effort required for setup. - Optimized Performance: Combining Nginx's high-performance web serving capabilities with PHP 7's improved execution speed ensures efficient handling of web requests. - Secure Configuration: The stack includes security enhancements, such as the ability to secure MySQL installations and manage user privileges effectively. - Scalability: Designed to operate seamlessly within the AWS ecosystem, the stack supports easy scaling to accommodate varying workloads. - User-Friendly Management: With default configurations like the web root set to `/usr/share/nginx/html`, users can quickly deploy and manage their PHP applications. Primary Value and Problem Solved: The LEMP Stack PHP 7 on Ubuntu addresses the challenges of setting up a reliable web server environment by providing a pre-configured, secure, and high-performance solution. It simplifies the deployment process, allowing developers to focus on building and managing their applications without the overhead of configuring and maintaining the underlying infrastructure. This solution is particularly beneficial for those seeking to deploy PHP-based web applications on AWS efficiently.

The PyTorch CPU MKL Notebook is a pre-configured, fully integrated runtime environment designed for machine learning and data science applications. It combines PyTorch, an open-source machine learning library for Python; Jupyter Notebook, a browser-based interactive notebook; and the Python programming language. Optimized for CPU performance, this stack also includes development tools such as a C compiler and make, facilitating efficient program development and execution. Key Features: - High-Performance Execution: Optimized for both training and inference tasks on CPU, ensuring efficient computation. - Integrated Software Packages: Includes carefully integrated and tested software with the latest features and bug fixes. - Stability and Support: Offers a stable, production-ready environment with long-term support and updates. Primary Value: The PyTorch CPU MKL Notebook simplifies the setup process for machine learning practitioners by providing a ready-to-use environment. This eliminates the complexities associated with configuring individual components, allowing users to focus on developing and deploying machine learning models efficiently. Its CPU optimization ensures that users can perform high-performance computations without the need for specialized hardware, making it accessible and cost-effective.

Postgres Pro 9.6 is an advanced, open-source relational database management system designed to handle a wide range of workloads, from single-machine applications to large-scale, multi-user environments. Building upon the robust foundation of PostgreSQL 9.6, Postgres Pro 9.6 introduces enhancements that improve performance, scalability, and usability, making it a reliable choice for developers and enterprises seeking a powerful database solution. Key Features and Functionality: - Parallel Query Execution: Utilizes multiple CPU cores to execute parallel sequential scans, joins, and aggregates, significantly improving query performance on multi-core servers. - Enhanced Synchronous Replication: Supports multiple synchronous standby servers, increasing data reliability and enabling consistent reads across database clusters. - Improved Full-Text Search: Introduces phrase search capabilities, allowing users to search for exact phrases or words within a specified proximity, enhancing text search functionality. - Foreign Data Wrapper Enhancements: Enables remote joins, sorts, and batch updates, facilitating efficient data federation and distribution of workloads across multiple PostgreSQL servers. - Advanced Indexing Options: Includes support for Bloom filters, providing efficient indexing for multi-column query conditions, and improves index-only scans for partial indexes. Primary Value and Problem Solving: Postgres Pro 9.6 addresses the challenges of managing high-performance, scalable, and reliable database systems. By leveraging parallel processing, it accelerates query execution, making it suitable for big data applications. The enhanced replication features ensure data consistency and availability, crucial for mission-critical applications. Improved full-text search capabilities cater to applications requiring advanced search functionalities. Overall, Postgres Pro 9.6 provides a comprehensive solution for organizations seeking a robust and scalable database system that can handle complex workloads efficiently.

AISE TensorFlow 1.10 Python 2.7 CPU MKL Production is a pre-configured Amazon Machine Image (AMI) designed to provide a robust and efficient environment for developing and deploying machine learning models. This AMI integrates TensorFlow 1.10, Python 2.7, and Intel's Math Kernel Library (MKL to optimize performance on CPU-based instances. It offers a stable and production-ready setup, enabling users to focus on building and training models without the overhead of manual configuration. Key Features and Functionality: - Pre-Configured Environment: Includes TensorFlow 1.10 and Python 2.7, eliminating the need for manual installation and setup. - Intel MKL Integration: Utilizes Intel's Math Kernel Library to enhance computational performance on CPU instances. - Stability and Support: Provides a stable, production-ready environment with long-term support and updates. - Development Tools: Comes with essential development tools, including a C compiler and build utilities, facilitating seamless development workflows. Primary Value and Problem Solved: This AMI addresses the challenge of setting up a high-performance, CPU-optimized environment for machine learning tasks. By integrating TensorFlow with Intel MKL, it significantly improves the efficiency of training and inference processes on CPU instances. Users benefit from a ready-to-use, stable platform that reduces setup time and allows them to concentrate on developing and deploying machine learning models effectively.

Spree is an open-source e-commerce platform built with Ruby on Rails, designed to provide businesses with a flexible and scalable solution for creating and managing online stores. Its modular architecture allows for extensive customization, enabling users to tailor the platform to their specific needs. Spree supports multi-store and multi-vendor marketplaces, making it suitable for a wide range of e-commerce applications. Key Features and Functionality: - Storefront Customization: Easily customize your homepage, product listings, and product detail pages. Use the default storefront or connect your own frontend application. - Multi-Region & Multi-Store Support: Manage unlimited products and variants individually or in bulk. Categorize, label, and add custom attributes. Generate gift cards or discounts with a robust promo rule engine. - Inventory Management: Manage stock levels across sales channels and locations. Track stock movements, receive stock, and make transfers. Make products available or discontinued on a given date. - Cart & Checkout: Customize checkout to reflect your business logic. Style it to be on-brand. Manage shipping and tax calculations. Enable fast checkout with Apple Pay or Google Pay. - Payments & Refunds: Capture payments with cards, Apple Pay, Google Pay, Buy Now Pay Later , local bank transfers, and redirects. Use one or multiple payment processors. Automate refunds. - Order & Return Management: Manage orders via the admin dashboard or rely on automated order processing. Use order splitting by vendor in a dropshipping model. Support partial or full returns and exchanges. - Order Fulfillment: Manage shipping across regions and warehouses. Use any shipping provider or aggregator. Track shipments in real-time with email notifications for customers. - Emails & Marketing Automations: Customize on-brand email notifications for customers around any order-related events. Automate post-purchase upselling, such as abandoned cart emails or other scenarios. - API & Integrations: Connect Spree to any custom user interface, such as a Next.js storefront or a mobile app. Integrate Spree with any system using APIs or webhooks, such as WMS, ERP, or CRM. Primary Value and User Solutions: Spree empowers businesses to build and manage customized e-commerce solutions that align with their unique requirements. Its open-source nature and modular design provide the flexibility to adapt and scale as businesses grow. By offering comprehensive features like multi-store support, advanced inventory management, and seamless integrations, Spree addresses the complexities of modern e-commerce, enabling users to deliver exceptional shopping experiences to their customers.

AISE PyTorch 0.4.1 Python 2.7 CUDA 9.2 Production is a pre-configured and fully integrated software stack designed for machine learning applications. It combines PyTorch 0.4.1, Python 2.7, and CUDA 9.2, providing a stable and optimized environment for developing and deploying deep learning models. This stack is tailored for high-performance tasks, ensuring compatibility and efficiency in both training and inference processes. Key Features and Functionality: - Pre-configured Environment: The stack comes fully integrated with PyTorch 0.4.1, Python 2.7, and CUDA 9.2, eliminating the need for manual setup and configuration. - High-Performance Execution: Optimized for both short and long-running tasks, the environment ensures efficient utilization of computational resources, particularly when leveraging GPU acceleration. - Stability and Reliability: Designed for production use, the stack offers a stable platform with long-term support and regular updates, ensuring consistent performance over time. Primary Value and Problem Solved: AISE PyTorch 0.4.1 Python 2.7 CUDA 9.2 Production addresses the complexities associated with setting up a compatible and efficient deep learning environment. By providing a ready-to-use, optimized stack, it allows developers and data scientists to focus on building and deploying machine learning models without the overhead of configuring and maintaining the underlying infrastructure. This solution is particularly beneficial for tasks requiring GPU acceleration, offering a seamless and efficient platform for deep learning applications.

The AISE PyTorch 0.4.1 Python 2.7 CUDA 9.2 Notebook is a pre-configured Amazon Machine Image (AMI) designed to facilitate deep learning development on AWS. It integrates PyTorch 0.4.1, Python 2.7, and CUDA 9.2, providing a ready-to-use environment for machine learning practitioners. This setup enables users to leverage GPU acceleration for training and deploying deep learning models efficiently. Key Features and Functionality: - Pre-Configured Environment: Combines PyTorch 0.4.1, Python 2.7, and CUDA 9.2, eliminating the need for manual installation and configuration. - GPU Acceleration: Utilizes CUDA 9.2 to harness GPU capabilities, significantly enhancing computational performance for deep learning tasks. - Jupyter Notebook Integration: Includes Jupyter Notebook, offering an interactive platform for coding, visualization, and documentation. - Amazon Linux 2018.03.0: Operates on a stable and secure Linux distribution, ensuring compatibility and reliability. Primary Value and Problem Solved: This AMI addresses the complexities associated with setting up a deep learning environment by providing a fully integrated and optimized platform. Users can focus on developing and training models without the overhead of configuring software dependencies. The inclusion of GPU support through CUDA 9.2 ensures faster execution times, making it ideal for computationally intensive tasks in machine learning and artificial intelligence projects.

Cogsult is an independent, vendor-neutral LIMS and lab informatics consulting practice. I help pharma, environmental, food and beverage, chemicals, manufacturing, and contract lab organizations select, implement, and optimize laboratory information management systems. My background includes 24+ years of hands-on WinLIMS/eLIMS platform experience, spanning both customer-side and vendor-side roles, along with deep regulatory grounding in 21 CFR Part 11, ISO 17025, and GAMP 5. Since I am vendor-independent, whether you are looking at LabVantage, Veeva, Labware, Confience eLIMS/WinLIM, MyLIMS, or smaller niche vendors, I can help. If you are starting, or even considering a LIMS project, let my experience become your advantage so that you get the right system to solve the right problem. Think. Plan. Deliver.

EB-5 Choice is a leading EB-5 investment advisor, helping investors secure U.S. permanent residency through the EB-5 Immigrant Investor Program. We assist high-net-worth individuals in accessing job-creating investment opportunities that fulfill USCIS requirements. As a trusted EB-5 investment advisor, EB-5 Choice provides expert guidance — from identifying compliant EB-5 projects to ensuring full adherence to immigration and financial regulations.

Gantway is web-based production planning and control software for workshops and small manufacturers with 5 to 50 employees: joineries, cabinet makers, interior fit-out, metal fabrication, locksmiths, furniture makers and other job-based production. Jobs, tasks, staff, machines and material live in one system. The scheduling board offers a board view and a Gantt view with drag and drop; tasks know their predecessors, so dependent dates recalculate on their own when a step moves. Conflict detection reports double bookings, overload, missing qualifications and material shortages, each with a suggested fix. The system also covers quotes with costing and a customer portal, material demand per job with purchasing, a time clock compliant with German working-time law, leave management, pre- and post-costing and a role-based dashboard. Staff without their own login are scheduled free of charge. Runs in the browser on PC, tablet and phone. Hosted in Germany, GDPR-compliant.

Vi förser ert företag med kunder från nätet. Vi tar bort er huvudvärken kring kundanskaffning online. Som webbyrå i Stockholm och Nacka bygger vi snabba, moderna och optimerade webbplatser, annonserar och lyfter dig i Google och Google Maps för en jämn ström av leads. Vi jobbar inte på löpande band. Antalet kunder är begränsat för kvalitet, personlig service och full uppmärksamhet på varje projekt. Effektivitet tack vare tio års erfarenhet och moderna AI-verktyg som ökar hastigheten och säkerställer kvalitetsresultat.

Jetware's LAMP Stack PHP 7 is a pre-configured environment designed for deploying web applications efficiently. It integrates the classic LAMP components—Linux, Apache HTTP Server, MySQL, and PHP—optimized with PHP version 7 to enhance performance and support modern web development needs. This stack simplifies the setup process, allowing developers to focus on building applications without the overhead of manual configuration. Key Features and Functionality: - Apache HTTP Server 2.4.25: Provides a robust and reliable web server platform. - MySQL 5.7.18: Offers a powerful relational database management system for data storage and retrieval. - PHP 7.1.4: Delivers improved performance and new features for dynamic web content. - phpMyAdmin 4.7.0: Facilitates database management through a user-friendly web interface. - Self-Management Preset: Includes tools and configurations for streamlined system administration. Primary Value and User Solutions: This LAMP Stack PHP 7 appliance addresses the common challenges of setting up a web development environment by offering a ready-to-use, optimized solution. It reduces deployment time, ensures compatibility between components, and enhances system performance. By providing a stable and production-ready platform, it enables developers and businesses to focus on application development and delivery, rather than infrastructure management.