Libraries tagged by order management

This module allow a admin user to come back to the same page(order, customer or config management) when it's session expires.

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This Extension integrates a credit check and more made by the LEONEX Risk Management Platform into your order process. Extensive configuration and evaluation options is provided in the Platform

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Resurs Bank - Order Management

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A fraud detection tool for e-commerce platforms to analyze customer order behavior across Steadfast and Pathao couriers.

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Symfony bundle for automatic sort order management in Doctrine ORM entities. Recalculates positions on flush with grouped ordering, second-level cache support, and PHP attribute configuration.

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Sales order management for Symfony2 applications.

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Laravel Admin Panel

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A powerful, flexible, and extensible e-commerce solution for Evolution CMS, designed to build modern online stores with product catalogs, shopping carts, checkout, order management, payments, APIs, and integrations.

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Use the official Picqer plugin to connect your Craft Commerce webshop to the Picqer warehouse management platform for efficient order handling.

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WISMOlabs Integration for Magento 2.4.7+, providing seamless order tracking, shipping notifications, and post-purchase marketing management.

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# Introduction **INDA (INtelligent Data Analysis)** is an [Intervieweb](https://www.intervieweb.it/hrm/) AI solution provided as a RESTful API. The INDA pricing model is *credits-based*, which means that a certain number of credits is associated to each API request. Hence, users have to purchase a certain amount of credits (established according to their needs) which will be reduced at each API call. INDA accepts and processes a user's request only if their credits quota is grater than - or, at least, equal to - the number of credits required by that request. To obtain further details on the pricing, please visit our [site](https://inda.ai) or contact us. INDA HR embraces a wide range of functionalities to manage the main elements of a recruitment process: + [**candidate**](https://api.inda.ai/hr/docs/v2/#tag/Resume-Management) (hereafter also referred to as **resume** or **applicant**), or rather a person looking for a job; + [**job advertisement**](https://api.inda.ai/hr/docs/v2/#tag/JobAd-Management) (hereafter also referred to as **job ad**), which is a document that collects all the main information and details about a job vacancy; + [**application**](https://api.inda.ai/hr/docs/v2/#tag/Application-Management), that binds candidates to job ads; it is generated whenever a candidate applies for a job. Each of them has a specific set of methods that grants users the ability to create, read, update and delete the relative documents, plus some special features based on AI approaches (such as *document parsing* or *semantic search*). They can be explored in their respective sections. Data about the listed document types can be enriched by connecting them to other INDA supported entities, such as [**companies**](https://api.inda.ai/hr/docs/v2/#tag/Company-Management) and [**universities**](https://api.inda.ai/hr/docs/v2/#tag/Universities), so that recruiters may get a better and more detailed idea on the candidates' experiences and acquired skills. All the functionalities mentioned above are meant to help recruiters during the talent acquisition process, by exploiting the power of AI systems. Among the advantages a recruiter has by using this kind of systems, tackling the bias problem is surely one of the most relevant. Bias in recruitment is a serious issue that affect both recruiters and candidates, since it may cause wrong hiring decisions. As we care a lot about this problem, we are constantly working on reduce the bias in original data so that INDA results may be as fair as possible. As of now, in order to tackle the bias issue, INDA automatically ignores specific fields (such as name, gender, age and nationality) during the initial processing of each candidate data. Furthermore, we decided to let users collect data of various types, including personal or sensitive details, but we do not allow their usage if it is different from statistical purposes; our aim is to discourage recruiters from focusing on candidates' personal information, and to put their attention on the candidate's skills and abilities. We want to help recruiters to prevent any kind of bias while searching for the most valuable candidates they really need. The following documentation is addressed both to developers, in order to provide all technical details for INDA integration, and to managers, to guide them in the exploration of the implementation possibilities. The host of the API is [https://api.inda.ai/hr/v2/](https://api.inda.ai/hr/v2/). We recommend to check the API version and build (displayed near the documentation title). You can contact us at [email protected] in case of problems, suggestions, or particular needs. The search panel on the left can be used to navigate through the documentation and provides an overview of the API structure. On the right, you can find (*i*) the url of the method, (*ii*) an example of request body (if present), and (*iii*) an example of response for each response code. Finally, in the central section of each API method, you can find (*i*) a general description of the purpose of the method, (*ii*) details on parameters and request body schema (if present), and (*iii*) details on response schema, error models, and error codes.

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Order & invoice management for Symfony, ideal for SaaS, services, and digital products.

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The Predefined Admin Order Comments module enhances Magento 2's order management by allowing administrators to quickly add standardized comments to orders. This module provides predefined comment templates that streamline communication, improve consistency, and save time when managing and processing orders within the admin panel.

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工单管理工具，小团队沟通工具。是作者平日的 laravel 框架研究中诞生的程序。该工具可用于团队之间的通知、BUG 报告、工作日报等等。

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Orders and payments management system in Laravel and the feature of adding sales functionality for each model

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