We’re excited to announce the general availability of the Kumo.AI platform, enabling the rapid creation and deployment of state-of-the-art AI models on private enterprise data. AI practitioners can now use our intuitive SQL-like Predictive Querying Language to build multiple task-specific AI models in a single day. The Kumo.AI platform empowers enterprises to unlock customer-focused use cases, such as personalization, churn and LTV prediction, fraud detection, and forecasting.

Streamline the machine learning process with Graph Neural Networks

While generative AI excels at natural language understanding and generation, it lacks the capability to perform more complex, enterprise-specific tasks, such as predicting customer behavior or detecting fraudulent transactions. Kumo.AI is the first platform that bridges this gap by applying deep representation learning, a technology behind the current AI revolution, to enterprise data. Our platform streamlines the most complex and time-consuming steps in the machine learning process by eliminating training data generation, feature engineering, feature pipelines, and feature stores. Just register your data schema and apply Kumo’s Graph Neural Networks, which generate predictions directly from your raw data tables, outperforming existing machine learning methods within days.

Designed for Scale, Speed, and Accuracy

We have built the most scalable and efficient graph learning platform, capable of generating predictions for hundreds of millions of entities, such as providing product recommendations for millions of users every day. Enterprises can leverage Kumo’s AutoML capabilities for an end-to-end automated experience or take full control of every step of the modeling process. Our advanced explainability tools offer insights into model behavior at both an aggregate population and an individual prediction level.

Seamless Integration and Deployment

The Kumo.AI platform is easy to set up and integrates seamlessly with a wide array of data sources, including the most common data warehouses and lakehouses. It ensures robust deployment in production, supported by REST APIs for programmatic orchestration, alongside comprehensive ML Ops monitoring dashboards, alerting systems, and lineage tracking functionalities. You can choose between a fully managed single-tenant SaaS offering or private deployment in Databricks and Snowflake environments, all backed by high availability SLAs and SOC 2 Type 2 compliance.

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