Libraries tagged by tracking code

Track e-mail delivery with Mailgun Hooks. All data are stored in the database on Email model

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Framework-free analytics and tracking tags for Contenir: tag definitions (Google tag, Tag Manager, Meta pixel, LinkedIn Insight), Consent Mode v2, ID validation and snippet rendering with a CSP nonce.

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The Tracking add-on for Contenir CMS: the Google tag, Tag Manager, the Meta pixel and LinkedIn Insight, with Consent Mode v2 and a per-environment switch. The reference add-on.

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Framework-free analytics and tracking tags for Contenir: tag definitions (Google tag, Tag Manager, Meta pixel, LinkedIn Insight), Consent Mode v2, ID validation and snippet rendering with a CSP nonce.

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A Laravel package for advanced logging, providing structured logs, contextual information, and customizable log channels.

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A powerful Laravel package for tracking, storing and comparing snapshots of your Eloquent models — cleanly and safely.

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Rinvex Statistics is a lightweight, yet detailed package for tracking and recording user visits across your Laravel application. With only one simple query per request, important data is being stored, and later a cronjob crush numbers to extract meaningful stories from within the haystack.

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The marketing fundamentals for a Statamic website: SEO, tracking tags, Consent Mode, favicons and redirects, Search Console numbers, site reports with a score and conversion events.

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AI backend for Laravel: provider/model catalog with pricing, request usage tracking and cost reporting, agent system-prompt registry and a self-updating tariff registry.

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Laravel package for managing enum-based model states with enforced transitions and automatic status history tracking.

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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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Modern inventory control for Laravel applications. Features include stock tracking, movement history, low stock alerts, and seamless integration with your existing models

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PHPStan extensions teaching shipmonk/dead-code-detector about lorisleiva/laravel-actions

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PHPStan extensions teaching shipmonk/dead-code-detector about Eloquent trait hooks and #[Scope] attributes

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Relationship-aware Eloquent model caching for Laravel with dependency tracking, cache tags, pagination-safe keys, and opt-in model APIs.

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