AthenaHQ
AthenaHQ is a powerful platform focused on Generative Engine Optimization (GEO), helping brands improve their AI search visibility and brand perception across AI-powered search engines. It offers tools to track brand mentions, identify gaps in AI-generated content, and enhance content to align with AI’s evolving preferences. With features like daily tracking, competitor analysis, and source intelligence, AthenaHQ provides actionable insights to help businesses stay relevant in an AI-dominated search landscape. The platform's AI-powered capabilities enable businesses to optimize content and drive more meaningful engagement through generative search.
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Action1
Action1 redefines patch management by enabling enterprises to rapidly discover and remediate vulnerabilities with a 99% patch success rate solution. Streamline your third-party patching, including custom software, through Action1’s Software Repository maintained in-house by security experts, and manage OS updates – fully integrated altogether with full feature-parity and uniformity.
Identify vulnerabilities in real-time and remediate them by applying available patches, removing unsupported or legacy software, or centralizing documentation of compensating controls for vulnerabilities that cannot be patched.
Optimize network traffic usage when large software packages up to 32Gb in size are deployed on the same network and deliver patches faster thanks to Action1’s P2P Distribution technology.
Action1 is the easiest-to-use patch management platform on the market, which you can set up in 5 minutes and automate your patching right away through its intuitive UI. Thanks to its cloud-native architecture, Action1 is infinitely scalable and works equally well for office-based and remote employee endpoints, servers, and cloud workloads, requiring no VPN.
Action1 is the first patch management vendor to achieve SOC 2, ISO 2
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Ansys VRXPERIENCE Driving Simulator
Explore a versatile, scalable, and modular virtual driving simulator that facilitates testing across diverse objectives and performance metrics. The Ansys VRXPERIENCE Driving Simulator, powered by SCANeR™, allows users to create scenarios, evaluate software, analyze vehicle dynamics, and engage with sensors all within a virtual driving framework. This simulator provides a complete virtual driving laboratory for scrutinizing performance outcomes. The VRXPERIENCE Driving Simulator delivers an engaging simulated driving experience situated in a realistic environment. Conduct thorough safety evaluations that enable the simulation of millions of virtual miles in just a few days, significantly accelerating development by a factor of 1,000 when compared to traditional road testing methods. As the landscape of passenger vehicles evolves to become increasingly digital and autonomous, the demand for an array of advanced technologies, including various sensors like cameras, radar, and lidar, as well as sophisticated embedded software for automated control systems, continues to grow. This advancement underscores the necessity for innovative tools in vehicle development and testing.
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NVIDIA DRIVE Map
NVIDIA DRIVE® Map is an advanced mapping platform crafted to support the utmost levels of vehicle autonomy while enhancing safety measures. By merging precise ground truth mapping with the agility and scale of AI-driven fleet-sourced mapping, it achieves remarkable results. The system utilizes four distinct localization layers—camera, lidar, radar, and GNSS—ensuring the necessary redundancy and flexibility for sophisticated AI drivers. With a focus on exceptional accuracy, the ground truth map engine generates DRIVE Maps by integrating a variety of sensors, including cameras, radars, lidars, and differential GNSS/IMU, all captured through NVIDIA DRIVE Hyperion data collection vehicles. It delivers an impressive accuracy of better than 5 cm, particularly in high autonomy scenarios (L3/L4), in environments like highways and urban areas. Designed for rapid operation and global adaptability, DRIVE Map leverages both ground truth and fleet-sourced information, encapsulating the shared knowledge of millions of vehicles on the road. This innovative approach not only enhances mapping precision but also contributes to the evolving landscape of autonomous driving technology.
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