Fraud.net
Fraudnet's AI-driven platform empowers enterprises to prevent threats, streamline compliance, and manage risk in real-time. Our sophisticated machine learning models continuously learn from billions of transactions to identify anomalies and predict fraud attacks.
Our unified solutions: comprehensive screening for smoother onboarding & improved compliance, continuous monitoring to proactively identify new threats, & precision fraud detection across channels and payment types. With dozens of data integrations and advanced analytics, you'll dramatically reduce false positives while gaining unmatched visibility. And, with no-code/low-code integration, our solution scales effortlessly as you grow.
The results speak volumes: Leading payments companies, financial institutions, innovative fintechs, and commerce brands trust us worldwide—and they're seeing dramatic results: 80% reduction in fraud losses and 97% fewer false positives.
Request your demo today and discover Fraudnet.
Learn more
Kubit
Your data, your insights—no third-party ownership or black-box analytics.
Kubit is the leading Customer Journey Analytics platform for enterprises, enabling self-service insights, rapid decisions, and full transparency—without engineering dependencies or vendor lock-in.
Unlike traditional tools, Kubit eliminates data silos, letting teams analyze customer behavior directly from Snowflake, BigQuery, or Databricks—no ETL or forced extraction needed.
With built-in funnel, path, retention, and cohort analysis, Kubit empowers product teams with fast, exploratory analytics to detect anomalies, surface trends, and drive engagement—without compromise.
Enterprises like Paramount, TelevisaUnivision, and Miro trust Kubit for its agility, reliability, and customer-first approach. Learn more at kubit.ai.
Learn more
Nixtla
Nixtla is a platform for time-series forecasting and anomaly detection built around its flagship model TimeGPT, described as the first generative AI foundation model for time-series data. It was trained on over 100 billion data points spanning domains such as retail, energy, finance, IoT, healthcare, weather, web traffic, and more, allowing it to make accurate zero-shot predictions across a wide variety of use cases. With just a few lines of code (e.g., via their Python SDK), users can supply historical data and immediately generate forecasts or detect anomalies, even for irregular or sparse time series, and without needing to build or train models from scratch. TimeGPT supports advanced features like handling exogenous variables (e.g., events, prices), forecasting multiple time-series at once, custom loss functions, cross-validation, prediction intervals, and model fine-tuning on bespoke datasets.
Learn more
