Harnessing AI and data science to transform complex challenges into actionable insights for impactful decision-making.
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Kubist combines AI, analytics, and expertise to tackle urgent issues—climate, healthcare, and policy—through data-driven solutions.
We transform complex data into structured, actionable insights to empower decision-making across industries.
Leveraging cutting-edge AI and deep domain knowledge, we create adaptable frameworks for large-scale challenges.
From climate and healthcare to policy, we apply data-driven strategies to address critical global issues.
We live in a time of unprecedented challenges from climate change and energy transition to politics, healthcare reform and education/training for a changing world. At the same time, we have a great resource which can help us imagine and build solutions: data. Data can ground us in fact and measure the value of solutions. This is even more important today than it has ever been, given our increasingly complicated media environment.
But data for good is not enough. The big problems are at such scale and so complex that the solutions need both a powerful technical environment, and an adaptable analytical approach that can take maximum advantage of this capability Kubist has developed such a framework. By leveraging the deep expertise of our founders, our goal is to help lead efforts to grapple with the most serious issues with a data-centered approach.
The relevant data often comes from many sources and often has a complex structure. We provide services to build accessible and queryable datasets based on the needs of our clients’ subject matter experts. Our team uses this querying capability to collaborate with our clients to deliver critical insights about their domain.
We take the next step of putting our tools in the hands of our clients, so that users can also explore and understand the data in their domain directly without relying on SQL experts. This avoids a critical bottleneck in most data science projects, and enables our approach to scale dramatically for our clients.
We augment the Build and Exploration framework using leading edge AI/ML to provide Discovery solutions that automatically identify relevant and actionable trends and patterns in the underlying data. This enriches the power of the framework and opens up enormous opportunities for extracting actionable insights.
Our capabilities deeply leverage our relationship with Claritype. Their platform is robust and effectively enables us to tackle the challenges we face in building and exploring.
Uses AI & Machine Learning to build complex datasets for in-depth analysis and data-driven decisions.
Provides direct access to the data via natural language and intuitive query construction tools.
To augment this technology Kubist brings our vast collective experience in delivering practical Data Science solutions. Technology is only as good as the real problems it solves for our clients. Our collaborative analytical expertise is key to addressing client questions and supporting their solutions engineering.
By working together with the Oaklandside team, we’ve built a structured queryable dataset that captures multiple aspects of the police pursuit experience. We used this asset together to jointly explore the underlying data. At the same time we provided Claritype’s Natural Language interface to the Oaklandside team directly, which they’ve used to deepen and broaden the insights they need.
The result is a penetrating analysis highlighting several of the most important factual issues that are outlined in the story above, helping to support the public debate on the topic.
Paul Stolorz is an accomplished technology executive and entrepreneur, with a world-wide reputation in the practical applications of Data Science at scale. He has built and led multiple global Product, Engineering and Data Science teams focussed on pioneering AI/ML solutions to compelling business challenges.
His experience covers key executive roles at companies ranging from internet giants to startups. These include Google, NASA’s Jet Propulsion Laboratory, where he led the Machine Learning Group for 5 years, Netflix, data.ai and as CEO and Cofounder of AI/ML startups. He holds a DIC degree in Mathematical Physics from Imperial College London, and a PhD in theoretical physics from the California Institute of Technology (Caltech).
Jeffrey is an experienced scientist and entrepreneur. He was a member of SRI’s Artificial Intelligence Center and helped manage large AI projects for DARPA. He has launched (founding CEO) and sold two AI companies, including a spinout from SRI. His background is in statistics and data mining and has a PhD in Applied Statistics from Columbia University.
Kubist is a 501(c)(3) nonprofit.
It was founded by Claritype, a company that is revolutionizing the way data science is done in enterprises.
