Libraries tagged by orders management
burnbright/silverstripe-shop
5126 Downloads
Provides an ecommerce product catalog, shopping cart, and order management system
inda-hr/php_sdk
835 Downloads
# 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.
chongyi/work-order-management
122 Downloads
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。
advancelearn/manage-payment-and-orders
12 Downloads
Orders and payments management system in Laravel and the feature of adding sales functionality for each model
tomatophp/tomato-orders
872 Downloads
full ordering and shipping system management with invoices templates for TomatoPHP
aimes/module-address-attributes-sort-order
199 Downloads
Allows re-ordering of checkout field from the customer address attribute admin management form.
shahariar-ahmad/courier-fraud-checker-bd
28 Downloads
A fraud detection tool for e-commerce platforms to analyze customer order behavior across Steadfast and Pathao couriers.
sylius/sales-bundle
13840 Downloads
Sales order management for Symfony2 applications.
kirago/laravel-business-core
50 Downloads
A Laravel business core multi-tenancies management data structure: orders, products, invoices, payments and more.
toteph42/isotope_stin
324 Downloads
Isotope EU STIN (Umsatzsteuer-ID) management for Contao.
t-shirt-and-sons/status-updates
494 Downloads
A package to handle status updates from T Shirt & Sons in your Laravel order management application.
mathcontao/be_piwikcharts
457 Downloads
Matomo (früher: Piwik)-Besucherstatistiken im Backend von Contao anzeigen. Extension for the Contao Open Source Content Management System in order to show Matomo statistics directly in the back end.
vismutx/klarna-order-management-api-php
23 Downloads
Klarna order management api for PHP generated by swagger
tomatophp/tomato-orders-module
201 Downloads
full ordering and shipping system management with invoices templates for TomatoPHP
thienhungho/yii2-order-management
25 Downloads
Yii2 Order Management