Kumo AI Wins Most Innovative AI Technology at 2024 A.I. Awards!
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Better AI Faster
Unlock your data warehouse with graph transformer architecture and pre-trained LLMs
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The technology behind ChatGPT, customized to work in your data warehouse
created in a single day
0 of Terabytes
scale graphs used as input
> 0 accuracy lift
versus in-house ML baselines
>$0 top-line impact
with multiple customers
Built by AI leaders from AirBnB, Google, LinkedIn, and Pinterest. Deployed and trusted by the world’s leading organizations.
Kumo and PyG Users
Get unprecedented value at a fraction of the cost
Better model performance
Leverage state of the art Graph Neural Networks to learn directly from your raw relational data without manual feature engineering, delivering dramatically higher accuracy
Cheaper
Simplify your infrastructure and optimize your costs by removing the need for feature pipelines, feature stores, etc.
Faster
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
Enterprise-ready
With REST APIs backed by high availability SLAs, SOC 2 Type II and GDPR compliance, options for both SaaS and Private Cloud operating models.
Kumo testimonials
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.
Marcus Fontoura
CTO at Stone Co.
Kumo has the potential to accelerate other projects within iFood. While we had a good recommendation system before, working with Kumo significantly enhanced our productivity.
We spent months developing our recommendation platform and graph model, but within a month, adding Kumo to our recommendation pipeline was much easier than any other model we have done in the past, and got better results in the end. In summary it was easier and faster than creating a model from scratch and gave us high quality recommendations.
By ensuring that our AI-driven recommendations are understandable and justifiable, we enhance user confidence and enable more informed decision-making.
Luiz Mendez
Head of Data Science
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.
Sergei Izrailev
Head of Analytics and Data Science
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