Operationalize Enterprise AI at Scale

Containerizing end-to-end end-points from data collection to data & feature engineering to ML scoring with a single command.

IT Leader
YOUR CHALLENGES

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.

MLOps Friendly

Operationalize containerized AI models on leading cloud MLOps platforms such as Amazon SageMaker with a single command.

Enterprise Ready

Deploy AI and ML development on a secure, scalable infrastructure in the cloud, on a private cloud, or behind the firewall.

Fast Tunnel

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.

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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.

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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.

Respected by Industry Experts

Named a leader by Forrester’s New Wave report for AutoML solutions. Forrester remarked that dotData was “AutoML’s best-kept secret.” and that it had the “unique ability to automatically generate new, transparent features across many data sets.”

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