Kumo Unveils KumoRFM
KumoRFM is trained on synthetic enterprise-like data, which makes the model compact and inference cost-effective.
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Kumo has announced the launch of KumoRFM, which allows businesses to generate predictions, such as item recommendations, identifying customer churn, or detecting fraudulent transactions, directly from their enterprise data.
KumoRFM gives organisations of any size an off-the-shelf, cost-effective AI model that eliminates the need to manually build and train separate models for each predictive task.
AI has completely transformed how businesses leverage text-based and unstructured data like documents, audio, video, and images. Yet, structured enterprise data, like customer records, transaction histories, and product catalogues, is the backbone of business decision-making, but remains largely untouched by this wave of AI innovation.
“To make predictions and business decisions, even the largest and most cutting-edge companies are using 20-year-old machine learning techniques on the enterprise data inside their data warehouses,” said Jure Leskovec, Co-Founder and Chief Scientist at Kumo.
“Extending Transformer architecture beyond natural language took significant innovation and investment. We’re proud to bring to enterprise data what GPTs brought to text, and at a fraction of the cost.”
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While language models such as ChatGPT use their understanding of semantic meaning within text to generate the next word, KumoRFM uses its understanding of traits, behaviours, and relationships represented inside data warehouses to predict what business outcomes will be at a different time or in a different scenario.
These predictions power business decisions, from flagging suspicious transactions to recommending products, personalising marketing offers, and selecting which ads or content to display.
Unlike traditional approaches that require building and training separate models for each such predictive task, KumoRFM enables accurate predictions without the need to even train or specialise the model. This shift allows AI and engineering teams to get predictions for different use cases in real-time, letting them explore and ship applications faster.
KumoRFM is trained on synthetic enterprise-like data, which makes the model compact and inference cost-effective.
“AI tools like chatbots and content generators have shown what’s possible with language, but there’s a missing piece when it comes to enterprise data, and KumoRFM fills that gap,” said Vanja Josifovski, Co-Founder and CEO at Kumo.
“The game changes completely when AI connects with business data. That’s when we see the needle move. Real numbers, real ROI, and real business impact.”
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