Libraries tagged by intelligent

helmich/mongomock

29 Favers
73170 Downloads

Library containing highly intelligent MongoDB mocks for unit testing

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cboxdk/laravel-queue-autoscale

8 Favers
2043 Downloads

Intelligent, predictive autoscaling for Laravel queues with SLA/SLO-based optimization

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byjg/serializer

6 Favers
191709 Downloads

A powerful multi-format serialization library that converts objects, arrays, and data between JSON, XML, YAML, CSV, PHP serialize, and plain text formats with intelligent property mapping and transformation

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b13/aim

25 Favers
602 Downloads

AiM - Intelligent AI proxy for TYPO3

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ashrafic/laravel-ai-orbit

32 Favers
205 Downloads

The Intelligent Control Tower for Laravel AI SDK.

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anteris-dev/autotask-client

24 Favers
58581 Downloads

This package provides a PHP API client for the Autotask REST API. It is strongly typed and it is a wonderful experience to work with these classes in any intelligent IDE with autocompletion.

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nystudio107/retour

168 Favers
18330 Downloads

Retour allows you to intelligently redirect legacy URLs, so that you don't lose SEO value when rebuilding & restructuring a website.

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trych/kirby-field-composer

24 Favers
761 Downloads

Kirby plugin providing methods to intelligently handle field values to compose complex strings.

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sunnysideup/vardump

0 Favers
2660 Downloads

Dev Module for intelligent Debugging

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sil-org/php-env

3 Favers
5129 Downloads

Simple PHP library for getting (or requiring) environment variables, designed to handle true, false, and null more intelligently. If desired, an environment variable's value can be split into an array automatically.

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rinvex/laravel-tenants

82 Favers
3491 Downloads

Rinvex Tenants is a contextually intelligent polymorphic Laravel package, for single db multi-tenancy. You can completely isolate tenants data with ease using the same database, with full power and control over what data to be centrally shared, and what to be tenant related and therefore isolated from others.

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prhost/packer

3 Favers
1169 Downloads

Library to organize and package your products intelligently

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jamierumbelow/pigeon

110 Favers
29250 Downloads

Intelligent, elegant routing for CodeIgniter

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inda-hr/php_sdk

6 Favers
1310 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.

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captcha-eu/typo3

0 Favers
23127 Downloads

Captcha.eu - The intelligent GDPR-compliant non-intrusive bot protection for your TYPO3 CMS Forms. Invisible/Non-interruptive - No riddles or puzzle solving neccessary!

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