Fraud.net
Fraud.net is the world's leading infrastructure for fraud management. It is powered by a sophisticated collective Intelligence network, world-class AI, and a modern cloud-based platform that assists you:
* Combine fraud data from all sources with one connection
* Detect fraudulent activity in real-time for transactions exceeding 99.5%
* Uncover hidden insights in Terabytes of data to optimize fraud management
Fraud.net was recognized in Gartner's market guide for online fraud detection. It is a real-time enterprise-strength, enterprise-strength, fraud prevention and analytics solution that is tailored to the needs of its business customers. It acts as a single point-of-command, combining data from different sources and systems, tracking digital identities and behaviors, then deploying the most recent tools and technologies to eradicate fraudulent activity and allow transactions to go through.
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Qloo
Qloo, the "Cultural AI", is capable of decoding and forecasting consumer tastes around the world. Privacy-first API that predicts global consumer preferences, catalogs hundreds of million of cultural entities, and is privacy-first. Our API provides contextualized personalization and insight based on deep understanding of consumer behavior. We have access to more than 575,000,000 people, places, and things. Our technology allows you to see beyond trends and discover the connections that underlie people's tastes in their world. Our vast library includes entities such as brands, music, film and fashion. We also have information about notable people. Results are delivered in milliseconds. They can be weighted with factors like regionalization and real time popularity. Companies who want to use best-in-class data to enhance their customer experiences. Our flagship recommendation API provides results based on demographics and preferences, cultural entities, metadata, geolocational factors, and metadata.
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Neuralhub
Neuralhub is a platform designed to streamline the process of working with neural networks, catering to AI enthusiasts, researchers, and engineers who wish to innovate and experiment in the field of artificial intelligence. Our mission goes beyond merely offering tools; we are dedicated to fostering a community where collaboration and knowledge sharing thrive. By unifying tools, research, and models within a single collaborative environment, we strive to make deep learning more accessible and manageable for everyone involved. Users can either create a neural network from the ground up or explore our extensive library filled with standard network components, architectures, cutting-edge research, and pre-trained models, allowing for personalized experimentation and development. With just one click, you can construct your neural network while gaining a clear visual representation and interaction capabilities with each component. Additionally, effortlessly adjust hyperparameters like epochs, features, and labels to refine your model, ensuring a tailored experience that enhances your understanding of neural networks. This platform not only simplifies the technical aspects but also encourages creativity and innovation in AI development.
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InQuanto
Quantum computing paves the way for the swift and cost-efficient creation of novel molecules and materials. InQuanto, an advanced platform for quantum computational chemistry, marks a significant advancement towards achieving this objective. The field of quantum chemistry seeks to precisely characterize and forecast the essential properties of matter, making it an invaluable asset for the innovation and formulation of new substances. Nonetheless, the intricacies of industrially relevant molecules and materials present challenges for accurate simulation. Current technologies necessitate a compromise, forcing users to choose between utilizing highly precise methods on minimal systems or resorting to approximations. InQuanto's adaptable workflow allows both computational chemists and quantum algorithm engineers to seamlessly integrate cutting-edge quantum algorithms with sophisticated subroutines and error mitigation techniques, optimizing performance on existing quantum platforms. This flexibility not only enhances research outcomes but also fosters collaboration among experts in the field, driving further innovation.
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