Generate and deploy highly accurate predictions in hours - not months
created in a single day
scale graphs used as input
versus in-house ML baselines
with multiple customers
Built by AI leaders from AirBnB, Google, LinkedIn, and Pinterest. Deployed and trusted by the world’s leading organizations.
for your mission critical use cases
Customer Retention & Next Best Action
Forecasting and Anomaly Detection
Entity Resolution and Knowledge Graph Enrichment
Fraud and Abuse Detection
Anti Money Laundering
Embeddings for Data Scientists
Leverage state of the art Graph Neural Networks to learn directly from your raw relational data without manual feature engineering, delivering dramatically higher accuracy
Simplify your infrastructure and optimize your costs by removing the need for feature pipelines, feature stores, etc.
Deliver ROI faster and across more use cases through our end to end platform covering all major steps in the ML lifecycle including data prep, model training, XAI, deployment, and ML Ops
with REST APIs backed by high availability SLAs, SOC2 compliance, options for both SaaS and Private Cloud operating models
Read about our platform capabilities in more detail
At Stone, we take pride in deeply understanding our small and medium-sized business customers and what they will do next. This allows us to provide them with products and services that provide the best value and thus retain them as customers for the long term.
A critical part of doing that is quickly implementing various highly accurate predictive models for many aspects of the customer journey, such as churn prediction, lifetime value, customer intent, and more.
Our data scientists loved Kumo's solution, which allows for a declarative way to specify modeling problems and for high iteration, excellent model performance, and a quick path to productization, thus increasing the productivity of these critical teams.
CTO at Stone Co.
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
Last month, Jure Leskovec, Co-founder and Chief Scientist at Kumo, unveiled the revolutionary Kumo.AI platform, marking a significant milestone in reshaping the landscape of the machine learning lifecycle.
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
Using AI and predictive machine learning (ML) to get actionable forward-looking insights from data are no longer a competitive edge, rather a necessity for ecommerce businesses. With so many options available, consumers expect high quality, personalized experiences that give them exactly what they are likely interested in.
Online food delivery is a massive market worth over $150B annually and growing at an exponential pace. With so much opportunity, competition is fierce - the market is incredibly fragmented, with new entrants coming in every year.
The world of ecommerce today is predominantly powered by machine learning to optimize the user experience and drastically improve how people interact with and consume goods and services.
The online gaming industry is one of the largest and most lucrative businesses in the world, projected to reach $321 billion in revenue by 2026.
Ecommerce has revolutionized the way we shop and interact with brands today. Within a few clicks, consumers can access a vast array of highly personalized products and services.
Every online and mobile game developer is familiar with the basic equation for successfully monetizing a game: CPI < LTV (i.e. you need to be able to generate more revenue from your players than it costs to acquire them).
Artificial intelligence is transforming industries across the globe, and personal finance is no exception. The sheer scale of financial data – from one billion daily credit card transactions to the 130 million Americans with personal loans – requires powerful predictive capabilities for financial service providers to find true signals in such noisy data.
We're excited to announce our partnership with Snowflake, the Data Cloud, with the common goal to democratize machine learning (ML) in the enterprise.
Kumo.ai presents an entirely new approach to performing machine learning at scale, one that drastically simplifies the end-to process and accelerates time-to-value.
In our digital world, privacy is always top of mind for consumers, vendors, and regulators. The digital landscape is constantly changing with respect to consumer data as policies like GDPR enforce limited tracking, and even more so with the Apple iOS 14 update implementing ATT, which enforces new data sharing policies.
Unleash the predictive power of your enterprise data
Recommendation systems are one of the most powerful tools that consumer marketplaces have available to them.
A leading US online personal finance & banking company wanted to improve revenue by doing targeted outreach to client’s users who might be interested in taking revenue-generating actions on their site – such as opening new accounts.
A Fortune 500 on-demand food delivery service wanted to increase its revenue by better personalizing their recommendations.
In an effort to help reduce customer churn and retain revenue, this payment company had built a retention team and created retention programs.
A leading grocery chain wanted to increase their sales by sending personalized physical flyers with a dozen coupons to their clients to encourage them to buy things they might want to buy.