Deploy AI Quickly & Easily With Automatic Containerization
Move AI models from development to production in record time by deploying containerized AI models as prediction microservices with a single Docker command. Enable real-time AI with milliseconds latency and enterprise-scale predictions across billions of transaction records.
End-to-End End-Point Production
Deploy end-to-end prediction end-points from data & feature engineering to ML scoring automatically with scalability and quality.
Operationalize containerized AI models on leading cloud MLOps platforms such as Amazon SageMaker with a single command.
Deploy AI and ML development on a secure, scalable infrastructure in the cloud, on a private cloud, or behind the firewall.
Continous AI Deployment
Integrate AI and machine learning models with speed and simplicity with dotData. Generate production-ready “full-cycle” end-points from data collection to data and feature engineering and ML scoring. Make enterprise deployments quickly and easily through enterprise-scale API end-points and containerized microservices.
Real-Time AI With dotData
dotData Stream allows you to deploy AI models in the most challenging real-time applications where millisecond predictions can make the difference between success and failure. Deliver AI on IoT Edge servers with a minimum resource footprint with dotData Stream.
Enterprise-Ready AI Automation
dotData supports enterprise-ready capabilities such as user management, process management, resource management as well as enterprise security, high availability, and scalability. Deploy on-premises, private cloud, or as dotData SaaS, based on your needs.
Automated Data Science empowers your business to build and benefit from predictive models
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