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What is Scalarr?

Scalarr presents an innovative solution for detecting mobile ad fraud by leveraging state-of-the-art Machine Learning technology. To address the most pressing issues in mobile advertising, Scalarr implements a dual-layered strategy featuring next-generation algorithms that boast an outstanding accuracy rate of up to 97% in recognizing various types of in-app fraud. Users can take advantage of Scalarr’s offerings by delving into its capabilities to monitor, assess, and prevent mobile app install ad fraud through its unsupervised machine learning functionalities before any damage occurs. The platform effectively employs both unsupervised and semi-supervised machine learning methods to autonomously identify and comprehend fraud patterns within extensive datasets. By analyzing numerous clicks, installs, and post-install event variables, Scalarr greatly reduces the occurrence of both false positives and false negatives in its detection framework. With a sophisticated model designed to prioritize accuracy and thoroughness, Scalarr emerges as a powerful tool that delivers actionable insights at the individual conversion level, enabling advertisers to make well-informed decisions about their ad campaigns. This holistic methodology not only fortifies the integrity of mobile advertising efforts but also empowers marketers to optimize their strategies for better performance and outcomes. Ultimately, Scalarr’s commitment to innovation ensures a safer advertising environment for all stakeholders involved.

What is Opticks?

Opticks emerges as a distinctive cybersecurity platform specifically designed for MVAS, Affiliate Networks, and Direct Advertisers, leveraging relentless artificial intelligence to maintain continuous surveillance. Its advanced and customizable analytics tools effectively detect various threats, including fraudulent subscriptions, automated bots, iFrames, malicious APKs, MSISDN, proxy traffic, harmful applications, and unsafe IP addresses. The seamless onboarding experience makes Opticks a top choice for forward-thinking companies around the world. This solution not only obstructs but also tracks complex forms of ad fraud in real-time, empowering users to swiftly recognize which traffic sources are poised to yield revenue while proactively preventing fraud. By supplying your growth teams with precise acquisition data, Opticks streamlines the fight against sophisticated online ad fraud, allowing you to confidently boost revenue. Our state-of-the-art technology is adept at revealing the most advanced fraud methodologies, with its adaptive machine learning features ensuring it remains ahead of malicious entities. Prepare to scrutinize the actual quality of your traffic, identify possible threats, and make well-informed decisions instantly, which will ultimately revolutionize your online advertising strategy. This innovative approach not only enhances security but also maximizes the effectiveness of your advertising efforts.

Media

Media

Integrations Supported

Adjust
AppsFlyer
Branch
Kochava
Singular
Tenjin
mParticle

Integrations Supported

Pushground

API Availability

API Availability

Pricing Information

Pricing not provided
Free Trial Offered?

Pricing Information

Pricing not provided

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
Web-Based Support

Training Options

Online Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Scalarr

Date Founded

2016

Company Location

United States

Company Website

scalarr.io

Company Facts

Organization Name

Opticks

Date Founded

2018

Company Location

Spain

Company Website

www.optickssecurity.com

Categories and Features

Ad Fraud Detection

Not specified

Click Fraud

Not specified

Categories and Features

Ad Fraud Detection

Not specified

Click Fraud

Account Alerts
Activity Monitoring
IP Address Monitoring
IP Blocking
Keyword Tracking
Risk Assessment

LiDAR

Not specified

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