Integrate ML models with your data
Kinetica seamlessly integrates machine learning models and algorithms with your data, for real-time predictive analytics at scale. By unifying the traditionally siloed workflows of analytics and model execution, Kinetica dramatically simplifies data engineering and active analytical application development.
Bring Your Own Algorithm
Bring your models to the data, not your data to the models. Bring existing models and analytics as containers and embed them into your analytical workflows and applications without the heavy lifting of migrating data to and from siloed model execution environments.AirBnb ML Pricing Demo
GPU-Accelerated Model Development with Kinetica + RAPIDS
Use the power of Kinetica to explore data interactively and generate features at scale, right from within a managed Jupyter Lab environment. Then, seamlessly transfer data to RAPIDS for accelerated training.RAPIDS Datasheet
Automated Deployment & Data Orchestration
Kinetica automates model deployment on Kubernetes – in continuous, on-demand or batch modes. No need to worry about deployment, network configuration, or scaling. Once deployed, Kinetica automatically orchestrates the full analytical pipeline – from ingest to database to model and back to database and downstream applications.
Track, govern, and audit data that’s part of your analytics and ML workloads. Kinetica tracks the full data lineage, including raw data, feature transformations, and model output. Easy-to-use search tool provides an instant ability to do a full model audit or find a “needle in a haystack” for a specific inference.Our chief product officer Irina Farooq discusses "Bringing AI Out of the Lab and Into Production" at ODSC 2019
Build Machine Learning into Active Analytical Applications
Deliver real-time experiences with the governance and ease of use you need to scale