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Fraud.netBest-in-class, Fraud.Net offers an AI-driven platform that empowers enterprises to combat fraud, streamline compliance, and manage risk at scale—all in real-time. Our cutting-edge technology detects threats before they impact your operations, providing highly accurate risk scoring that adapts to evolving fraud patterns through billions of analyzed transactions. Our unified platform delivers complete protection through three proprietary capabilities: instant AI-powered risk scoring, continuous monitoring for proactive threat detection, and precision fraud prevention across payment types and channels. Additionally, Fraud.Net centralizes your fraud and risk management strategy while delivering advanced analytics that provide unmatched visibility and significantly reduce false positives and operational inefficiencies. Trusted by payments companies, financial services, fintech, and commerce leaders worldwide, Fraud.Net tracks over a billion identities and protects against 600+ fraud methodologies, helping clients reduce fraud by 80% and false positives by 97%. Our no-code/low-code architecture ensures customizable workflows that scale with your business, and our Data Hub of dozens of 3rd party data integrations and Global Anti-Fraud Network ensures unparalleled accuracy. Fraud is complex, but prevention shouldn't be. With FraudNet, you can build resilience today for tomorrow's opportunities. Request a demo today.
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ManageEngine Log360Log360 is a comprehensive security information and event management (SIEM) solution designed to address threats across on-premises, cloud, and hybrid environments. Additionally, it assists organizations in maintaining compliance with various regulations like PCI DSS, HIPAA, and GDPR. This adaptable solution can be tailored to fit specific organizational needs, ensuring the protection of sensitive information. With Log360, users have the ability to monitor and audit a wide range of activities across their Active Directory, network devices, employee workstations, file servers, databases, Microsoft 365, and various cloud services. The system effectively correlates log data from multiple sources to identify intricate attack patterns and persistent threats. It includes advanced behavioral analytics powered by machine learning, which identifies anomalies in user and entity behavior while providing associated risk scores. More than 1000 pre-defined, actionable reports present security analytics in a clear manner, facilitating informed decision-making. Moreover, log forensics can be conducted to delve deeper into the origins of security issues, enabling a thorough understanding of the challenges faced. The integrated incident management system further enhances the solution by automating remediation responses through smart workflows and seamless integration with widely used ticketing systems. This holistic approach ensures that organizations can respond to security incidents swiftly and effectively.
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TrustInSoft AnalyzerTrustInSoft has developed a source code analysis tool known as TrustInSoft Analyzer, which meticulously evaluates C and C++ code, providing mathematical assurances that defects are absent, software components are shielded from prevalent security vulnerabilities, and the code adheres to specified requirements. This innovative technology has gained recognition from the National Institute of Standards and Technology (NIST), marking it as the first globally to fulfill NIST’s SATE V Ockham Criteria, which underscores the significance of high-quality software. What sets TrustInSoft Analyzer apart is its implementation of formal methods—mathematical techniques that facilitate a comprehensive examination to uncover all potential vulnerabilities or runtime errors while ensuring that only genuine issues are flagged. Organizations utilizing TrustInSoft Analyzer have reported a significant reduction in verification expenses by 4 times, a 40% decrease in the efforts dedicated to bug detection, and they receive undeniable evidence that their software is both secure and reliable. In addition to the tool itself, TrustInSoft’s team of experts is ready to provide clients with training, ongoing support, and various supplementary services to enhance their software development processes. Furthermore, this comprehensive approach not only improves software quality but also fosters a culture of security awareness within organizations.
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FinOpslyAsk a CFO what the company spent on AI last quarter and you will get a number. Ask which product line it belonged to, whether anyone approved it, or what it earned, and the room goes quiet. FinOpsly was built for that second set of questions. It is an AI Cost Governance platform. AI does not run in isolation, so FinOpsly does not price it in isolation either. A model call pulls warehouse queries, GPU time and storage behind it, and the engineers building the feature are burning licensed seats the whole time. All of that lands in one cost model, mapped to the company's own structure: owner, team, product, business unit, customer. What teams use it for: Pricing a workload before anyone provisions anything. Describe the architecture, get a cost estimate across the stack, and see which assumptions drove it. Compare model options using consumption you have already paid for. Making chargeback something finance trusts. Hierarchies run nine levels or deeper. Tags get standardized across providers that never agreed on a convention. API keys and resources are labeled in bulk from instructions written in ordinary English. Anything still unowned shows up as a dollar figure. Holding the line during the month. Budgets by team, project or key. Anomalies flagged with a root cause and sent to the person responsible. Waste that provider consoles do not catch, found by FinOpsly's own detection models. Idle compute parked on schedules the customer approved, and reversible. Proving the outcome. One chargeback run covering AI, cloud, data and SaaS together. Savings measured against the base-line along with cost-to-serve metrics: cost per active user, per customer served. Customers have moved attributable spend from 68% to 99% inside 90 days and taken a chargeback cycle from 12.4 days down to under one. Built for CIOs, CTOs, FinOps practitioners and the finance teams who sign off on the bill.
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Splashtop Autonomous Endpoint ManagementSplashtop's Autonomous Endpoint Management provides an automated solution for managing endpoints, specifically designed to aid IT teams in overseeing, securing, patching, and controlling devices remotely, all while minimizing manual involvement. This innovative approach offers instant insights into the health of devices, automates the patching for both operating systems and third-party applications, and maintains compliance in multi-location environments. With features like secure remote access and real-time patch management, it integrates seamlessly with platforms such as Microsoft Intune to quickly pinpoint and mitigate zero-day vulnerabilities. Centralized dashboards allow for a holistic overview of inventory, security metrics, and the status of endpoints, enabling IT teams to proactively tackle issues before they impact users, all while ensuring compliance with vital regulations like ISO/IEC 27001, SOC 2, GDPR, HIPAA, and PCI. Moreover, AEM simplifies standard operations, including patch deployment and system updates, which frees up IT staff from tedious tasks and allows them to concentrate on more sophisticated problems. As a result, this cutting-edge endpoint management solution not only boosts operational efficiency but also strengthens an organization’s security framework while facilitating a more agile response to emerging threats.
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OvermonitorOvermonitor is a cloud-based website, server, infrastructure, and endpoint monitoring platform designed for businesses that need reliable uptime visibility without enterprise-level complexity. It helps IT teams, SaaS operators, managed service providers, developers, and small businesses monitor website availability, response time, SSL certificates, server health, endpoint status, Windows services, running processes, event logs, and internal network availability from one centralized dashboard. Unlike basic uptime monitoring tools that only check public URLs, Overmonitor can also use a small, lightweight server agent that installs quickly, pairs with your account, and reports a heartbeat every minute from inside your network. This provides deeper visibility into endpoint health, service failures, process problems, internal outages, and infrastructure issues that may not be visible from the outside. Overmonitor includes city-level geotargeted monitoring, practical maintenance windows, push notifications, audible dashboard alerts, process monitor rollups, embeddable performance graphs, and flexible à la carte pricing. These features make it easier to reduce alert noise, share performance data, identify outages faster, and understand the real-world reliability of your websites, servers, and services. Built as a simpler alternative to bloated monitoring suites, Overmonitor focuses on fast configuration, actionable alerts, lightweight deployment, and clear operational visibility. Use Overmonitor to detect downtime, troubleshoot infrastructure problems, monitor endpoint performance, and improve end-user experience before small issues become major business interruptions.
What is Amazon Lookout for Metrics?
To effectively detect irregularities in business metrics, it is crucial to minimize false positives through the application of machine learning (ML). By clustering similar outliers, one can delve into the root causes of these anomalies for a thorough examination. Summarizing these underlying issues and ranking them based on severity ensures that organizations can address the most critical problems first. The integration with AWS databases, storage solutions, and third-party SaaS applications enables ongoing monitoring of metrics and anomaly detection. Additionally, implementing customized automated alerts and responses when anomalies are detected boosts operational efficiency significantly. The Lookout for Metrics tool employs ML to automatically identify anomalies in both business and operational data, while also uncovering their root causes. Detecting unexpected anomalies poses a challenge, especially since conventional methods typically depend on manual processes that often introduce errors. Lookout for Metrics alleviates this complexity, empowering users to identify and analyze data inconsistencies without specialized knowledge in artificial intelligence (AI). Furthermore, this tool enables the monitoring of unusual variations in subscriptions, conversion rates, and revenue, promoting a proactive stance against sudden market shifts. By harnessing sophisticated machine learning approaches, businesses can greatly enhance the precision of their anomaly detection endeavors, ultimately leading to better decision-making and more resilient operations. This strategic application of technology thus not only improves detection but also fosters a culture of continuous improvement within organizations.
What is Actian Data Observability?
Actian Data Observability is a cutting-edge platform that utilizes artificial intelligence to continuously monitor, validate, and uphold the integrity, quality, and reliability of data within modern data ecosystems. This platform features automated Data Observability Agents that evaluate the data as it flows into data lakehouses or warehouses, allowing for the detection of anomalies, clarification of root causes, and support for problem-solving before these issues can disrupt dashboards, reports, or AI applications. By offering real-time insights into data pipelines, it ensures that data remains accurate, complete, and trustworthy throughout its lifecycle. In contrast to conventional techniques that rely on sampling, this system eliminates blind spots by overseeing the full spectrum of data, enabling organizations to identify hidden errors that could undermine analytics or machine learning outcomes. Additionally, its built-in anomaly detection, powered by AI and machine learning, facilitates the prompt identification of irregularities, such as schema changes, data loss, or unexpected distributions, which accelerates the diagnosis and rectification of issues. Ultimately, this forward-thinking methodology greatly increases the confidence organizations have in their data-driven decisions, fostering a culture of data reliability and integrity. Furthermore, as companies continue to depend on data for strategic planning, such a robust observability framework becomes indispensable in navigating the complexities of today’s data landscape.
Integrations Supported
Amazon Redshift
Amazon S3
Amazon CloudWatch
Amazon Simple Notification Service (SNS)
Integrations Supported
Amazon Redshift
Amazon S3
Apache Hudi
Apache Spark
Asana
Delta Lake
Google Analytics
Google Cloud BigQuery
API Availability
Has API
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
Documentation Hub
Webinars
Training Options
Documentation Hub
Webinars
Online Training
Company Facts
Organization Name
Amazon
Date Founded
1994
Company Location
United States
Company Website
aws.amazon.com/lookout-for-metrics/
Company Facts
Organization Name
Actian
Date Founded
1980
Company Location
United States
Company Website
www.actian.com/data-observability/
Categories and Features
Machine Learning
Not specified
Categories and Features
Data Observability
Not specified