Applied AI for everyone, with a twist.
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WE DEVELOPED A NUMBER OF TOOLS & PRINCIPLES BUILT FROM BEST PRACTICE
Build from Data Kinetic's proprietary research into capability measures for key parts of AI infrastructure, data platforms, business systems design, and AI strategy.
A shocking large number of Applied AI projects fail or get stuck just before the finish line. And it's not for the reasons you might think. Often it comes down to building compounding outcomes rather than trying to solve everything at once. We help you prioritize and build high business value outcomes, while building out your Applied AI governance and systems of record.
We know this is the fun part, but often this is also the stage where critical decisions need to be made. Data Kinetic partners with you to ensure that those considerations are included up front, avoiding costly delays as you get closer to production, and assuring that the project remains in line with business expectations.
Data Kinetic has over 100+ application blueprints that we offer to support customers building their application. Take the guess work out of requirements and design stages to ensure that key technologies are validated up front. We regularly update these with new techniques as the market rapidly evolves.
HEAR FROM THOSE THAT COUNT
We've been working on Applied AI problems for over a decade. Hear from experts on how Data Kinetic can help you.
"In the high-stakes environment of the operating room, where split-second decisions can mean the difference between life and death, the team at Data Kinetic is making significant strides in applying artificial intelligence to improve patient outcomes in cardiac surgery.
Under the leadership of Nick and Gonzo, Data Kinetic has distinguished itself by deeply engaging with the unique challenges and constraints of the surgical domain. Their commitment to understanding the intricacies of cardiac surgery has allowed them to develop AI solutions that deliver tangible impact, setting a new standard for the effective application of AI in healthcare.
Data Kinetic's work underscores the importance of interdisciplinary collaboration in driving meaningful advancements in medical AI. By bringing together experts in machine learning, software engineering, and clinical practice, they have created tools that provide surgeons with actionable insights and support when it matters most.
As the field of healthcare AI continues to evolve, the success of teams like Data Kinetic highlights the need for more focused, domain-specific approaches that prioritize real-world impact over hype. By cutting through the noise and focusing on the specific needs of clinicians and patients, they are laying the groundwork for AI to transform patient care across a wide range of medical specialties.
In the years to come, the work of Data Kinetic and other pioneering teams will be instrumental in realizing the full potential of AI in medicine. Their dedication to bridging the gap between cutting-edge technology and clinical practice offers hope for a future in which AI-powered tools become an integral part of the surgical arsenal, helping to save lives and improve outcomes for patients around the world."
& Director of Artificial Heart, Mechanical Circulatory Support, and ECMO
WE TOOK EVERYTHING WE HATED ABOUT TODAY'S TECHNOLOGY LANDSCAPE AND FIXED IT
After years of working for large AI companies we all got together and came up with a new way of getting AI to production. Focusing not just on amazing technologies, but also the requirements to get the job done. No extended evaluation cycles, No forever costs associated with delivery. No vendor lock-in.
MEET SOME OF THE TEAM
Built and developed multiple categories including Azure SQL, Google Cloud AI, Android Enterprise, DataRobot.
Nick has 20 years experience in enterprise and government Applied AI use cases. He focuses primarily on regulated industries with specific bodies of research in healthcare, oil & gas, supply chain, and decision intelligence.
David “Gonzo” González co-founded Zeff.ai, acquired in 2020 by Boston-based DataRobot where he succeeded in bringing a jobs-to-be-done perspective to focus product strategy.
Gonzo pioneered transactionally authored training and inference on multi-modal datasets and is the primary author of The AI Manifesto for Applied Artificial Intelligence Development and has multiple ML patents.
AI/ML Engineer and Data Scientist specializing in arbitrage and complex hierarchical forecasting and prediction.
Nathan primarily focuses on developing production ready ML systems for regulated industries.
Over 30 years of experience in software design and innovation. Written thousands of lines of code, launched products, raised funding, and spent 5 years as a Gartner analyst.
He consults, writes, and lectures widely on software development, mobile, low code, web tools and AI with a flair for bringing the hype down to earth and helping clients become smarter innovation adopters.
Director of Data Science - ML/AI at Microsoft. Founding member of Microsoft AI initiatives from 2006 - 2020 (retired).
Jim has come out of retirement to work on Data Kinetic’s unique healthcare problems and brings a wealth of healthcare AI use cases in production knowledge.
Applied AI data scientist currently studying in Berkeley in AI and Computer Science.
Abhijith is a generative AI specialist and focuses on model augmentation and scaled Applied AI design.
Applied AI data scientist currently studying in Berkeley in AI and Computer Science.
Atharva is studying supply chain models and optimization with physics models and supporting simulations.
As a digital twin thought leader Mark cascading benefits and ecosystem challenges, and the ultimate goal of predictive decision-making at all levels of an organization.
Steffin is an energetic, results-driven visionary and transformational leader with nearly 30 years of technology and business experience.
Attributing his success working for great managers, leading phenomenal teams, learning from his partners/peers to work smarter and frankly timing.