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Data Kinetic

Data Kinetic

Technology, Information and Internet

Austin, Texas 879 followers

A platform-agnostic catalog of industry-specific machine-learning outcomes-as-a-service that run in your environment.

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About us

🦾The Problem: Creating true in-production AI applications is incredibly complex. The implications for misconfiguration are real, and the traditional approach for building non-AI applications doesn’t translate well into AI/ML. Beyond MLOps and the great toolchains, there needs to be a deeper approach to cater to solving today’s toughest enterprise challenges. 🔍 What is Data Kinetic? Data Kinetic provides a catalog of industry-specific machine-learning models as a subscription service. Our advisory, delivery, and R&D company is committed to delivering applied AI outcomes for industries. We focus on driving meaningful impact by combining modern and proven AI/ML techniques and directly enabling them within existing business systems. 🔬 R&D: Our research concentrates on novel data management and augmentation, LLM/generative use cases for enterprises, and emerging AI techniques such as declarative AI, model performance enhancement, and fit-for-purpose AI agents. 🔧 Platform Agnostic: We'll build on your existing investments. Data Kinetic is designed to work on top of your data infrastructure and build solution outcomes that align the business to deliver direct impact. We actively work with several of the largest AI, Data, and Platform companies to ensure we elegantly work with their technology investments and innovations. 🌐 Applied AI Expertise: Data Kinetic will guide customers and partners through AI adoption, outcome-specific solutions, training, and access to our R&D frameworks when applicable. We'll also help enterprises develop effective strategies, stay ahead of regulations, and choose projects with direct outcomes.

Website
https://www.datakinetic.com
Industry
Technology, Information and Internet
Company size
2-10 employees
Headquarters
Austin, Texas
Type
Privately Held
Founded
2023

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  • View organization page for Data Kinetic
    Data Kinetic

    879 followers

    Nicholas King is back on the road catch him at NYU in April.

    View profile for Nicholas King
    Nicholas King

    Applied AI | Industry Solutions | GTM & Growth | Digital Transformation | Marketing & Product Leadership

    Coming out of my LinkedIn Hiatus, I'm excited to share that I’ll be a joining the team at NYU to be a PANEL MEMBER at the AI Masterclass from April 25-27, 2025—a live workshop designed for Board Members, C-Suite Executives, & Senior Leaders. This masterclass brings together top AI minds, featuring Aditya (Ed) Watal — Lead Faculty, Founder & Principal at Intellibus, and 🦾Jepson Taylor — Co-Faculty, Former Chief AI Strategist at Dataiku & AI Startup Founder. This is one of my favorite forums where leaders get together and share fresh insights, connecting with like-minded leaders, and exploring how we can not just adapt to AI—but lead with it.  Learn more: www.aimasterclass.com #AIMasterclass #ArtificialIntelligence #Leadership #AIInnovation #FutureReady #TechLeadership

  • View organization page for Data Kinetic
    Data Kinetic

    879 followers

    Here at Data Kinetic, we work with clients to apply AI in complex decision making for healthcare, oil & gas, and supply chain domains. The team is always looking for ways to improve the quality of analysis and interactions. What we’ve seen is that using a mix of models, each the best fit for a specific task, allows us better control over outcomes than a single monolithic model. Amazon Bedrock is a perfect match for our architecture and security needs. It allows us to mix and match models as we need, all within the same API interface and with the same control mechanisms. We recently completed an evaluation of Amazon Nova Pro and have now added it to our production deployment. Alongside being really fast, Amazon Nova Pro provides predictable and consistent responses in scenarios. This is critical for us in order to deliver the quality and consistency needed in our clients’ analyses. We were initially excited about Amazon Nova models because of their speed. During evaluations, the consistency and quality has outperformed our expectations and has been a pleasant surprise. Using the security and IAM tooling on Amazon Bedrock, we have been able to easily apply our access policies and get this into production in our studio. We’re now looking at additional use cases where Amazon Nova models can be applied to improve the speed and overall quality of analysis. Learn more about how we are using generative AI at our upcoming webinar on Generative AI on AWS on March 20th, 2025. https://lnkd.in/gA27yvMm

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