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Deliver predictive analytics across your enterprise in days, regardless of your ML experience
We automate all major steps in the ML lifecycle from raw data ingestion to sustained production deployment
Query the future in our ‘Predictive Querying’ language that is as easy to use as SQL
Leverage automated machine learning with state of the art Graph Neural Network technology to drive higher accuracy even with less data
Deliver more predictions more quickly across every team, enabling your entire enterprise to more proactively choose the future you want
One platform
Customer Acquisition
Customer Retention and Next Best Action
Personalization
Forecasting and Anomaly Detection
Entity Resolution and Knowledge Graph Enrichment
Fraud and Abuse Detection
Anti Money Laundering
Embeddings for Data Scientists
Read about our platform capabilities in more detail
At Whatnot, AI plays a critical role in personalizing the shopper experience, driving cross-sell across categories and predicting future aggregate shopper behavior so we can shape our broader marketplace.
To this end, we are working with Kumo to deliver a service that is truly ground-breaking, allowing us to not only quickly launch these needed predictions with their very simple predictive querying language and accompanying APIs, but also drive dramatic model quality gains, including a doubling of both precision and recall over existing baselines in initial experiments. We've been thrilled by the progress so far, and the ability of the Kumo product to allow even non-technical teams to harness the power of AI from our data in the future.
VP of Engineering at Whatnot
At Yieldmo, we are hyper focused on cutting edge AI approaches to maximize the value of advertising for buyers, sellers, and consumers in a privacy-first way.
Our recent collaboration with the Kumo team offers us the opportunity to leverage their innovative graph neural network technology within our next-generation machine learning (ML) models for ad inventory curation.
So far, the early results have been very promising, showing a significant improvement in predictive power compared to leading solutions in the market today.
Head of Analytics and Data Science
Graph neural networks (GNNs) have emerged as one of the leading solutions for ML applications. Most real-world data can be represented as graphs - see this blog for a comprehensive overview of what use cases are best solved with GNNs and their key advantages.
In this post, we’ll paint a picture of how effective graphs are in representing many real world problems, most likely including many of the business problems you face.
Kumo, a startup offering an AI-powered platform to tackle predictive problems in business, today announced that it raised $18 million in a Series B round led by Sequoia, with participat...
Founded by former executives at Airbnb, Pinterest, LinkedIn, and Stanford University, Kumo recently launched their next-generation approach to AI over cloud based data...
Our vision is simple: to make it as easy for you to ‘Query the Future’ as it is for you to query the past using SQL on historic data today. All enabled by the cutting edge of deep learning innovation.
Founded by pre-eminent researchers and executives from companies and academic institutions including Airbnb, Pinterest, LinkedIn, Stanford University, and more, the start-up is taking a next-generation approach to predictive AI.
When I met Jure Leskovec eight years ago in a Stanford classroom, it was immediately clear that he was special.
Modern businesses possess complicated networks of data, connecting information like customer behavior to marketing campaigns or fraud detection.
Unleash the predictive power of your enterprise data