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csideEffectively tracking third-party scripts removes ambiguity, guaranteeing that you remain informed about what is sent to your users' browsers. The uncontrolled existence of these scripts within users' browsers can lead to major complications when issues arise, resulting in negative publicity, possible legal repercussions, and claims for damages due to security violations. Organizations that manage cardholder information must adhere to PCI DSS 4.0 requirements, specifically sections 6.4.3 and 11.6.1, which mandate the implementation of tamper-detection mechanisms by March 31, 2025, to avert attacks by alerting relevant parties of unauthorized changes to HTTP headers and payment details. c/side is distinguished as the only fully autonomous detection system focused on assessing third-party scripts, moving past a mere reliance on threat intelligence feeds or easily circumvented detection methods. Utilizing historical data and advanced artificial intelligence, c/side thoroughly evaluates the payloads and behaviors of scripts, taking a proactive approach to counter new threats. Our ongoing surveillance of numerous websites enables us to remain ahead of emerging attack methods, as we analyze all scripts to improve and strengthen our detection systems continually. This all-encompassing strategy not only protects your digital landscape but also cultivates increased assurance in the security of third-party integrations, fostering a safer online experience for users. Ultimately, embracing such robust monitoring practices can significantly enhance both the performance and security of web applications.
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What is Two Hat?
A specialized neural network has been created to streamline the process of triaging reported content online. For years, social media platforms have relied on users to report abusive conduct, hate speech, and various forms of online harm. These flagged reports are then sent to moderation teams that evaluate each one individually. Many platforms face a deluge of reports on a daily basis, with a considerable number being resolved without any further action taken. However, reports concerning urgent issues—such as suicidal threats, violent incidents, terrorism, or child exploitation—may be at risk of being ignored or addressed too slowly. Such delays can lead to severe legal consequences as well. In accordance with the German law known as NetzDG, social media companies must remove reported hate speech and illegal content within a 24-hour window, or they could face fines of up to 50 million euros. As similar laws regarding reported content are emerging in nations like France, Australia, and the UK, the demand for efficient moderation methods is becoming increasingly paramount. The Predictive Moderation product from Two Hat enables platforms to create a custom AI model that learns from the consistent decisions of their moderation teams, thus improving both the speed and accuracy of responses to urgent reports. This advancement not only bolsters user safety but also aids platforms in effectively navigating the intricate landscape of legal compliance. Furthermore, it represents a significant step forward in the ongoing effort to maintain online communities that are both safe and respectful for all users.
What is Laya AI?
Laya AI embodies a collection of open-source, non-autoregressive decision-making models that prioritize swift and structured decision processes over the generation of free-form text. By analyzing a specific state alongside structured queries in one comprehensive step, it generates outputs that can be seamlessly integrated into application code. The system categorizes decisions into three types: choice, which selects from a set of predefined options and provides associated probabilities; score, which evaluates an input on a ranked scale such as urgency or severity; and noul, which predicts the likelihood that a statement is true. Designed for a wide range of tasks, Laya effectively manages agent and model routing, assists in ticket triage, and conducts risk assessments, among other functionalities. Its features enable the system to allocate requests to the correct department, gauge urgency levels, detect signs of potential refunds or customer churn, and identify instances of policy breaches or abuse. Additionally, it can escalate unclear cases to more sophisticated models or human experts for further examination. This adaptability makes Laya AI not only a valuable tool in operational settings but also enhances its ability to evolve with the changing demands of various industries. Ultimately, Laya AI distinguishes itself through its remarkable versatility and effectiveness in enhancing decision-making processes across a plethora of operational requirements.
Integrations Supported
API Availability
Has API
API Availability
Has API
Pricing Information
Pricing not provided
Pricing Information
Free
Free Version
Supported Platforms
SaaS
Supported Platforms
Windows
Mac
Linux
Customer Service / Support
Standard Support
Web-Based Support
Customer Service / Support
Web-Based Support
Training Options
Documentation Hub
Webinars
Online Training
Training Options
Documentation Hub
Company Facts
Organization Name
Two Hat
Date Founded
2012
Company Location
Canada
Company Website
www.twohat.com/predictive-moderation-template/
Company Facts
Organization Name
Laya AI
Date Founded
2020
Company Location
India
Company Website
laya-ai.com
Categories and Features
Content Moderation
Not specified
Categories and Features
AI Decision Models
Not specified