Introducing Cloud-native ML Ops

Automate your ML deployment process quickly, safely, and at scale.

Seamlessly build, train, deploy, manage and monitor your ML models/pipelines at scale - on any infrastructure

Dataspine enables machine learning engineers, data scientists and dev/ops teams to accelerate the end-to-end lifecycle for AI/ML -- through powerful, composable and self-serve tools -- without the in-house engineering and infrastructure overhead.

Our enterprise-grade solution runs on any cloud, hybrid or on-premise environment - and you keep full control over your data, models, and stack.

Dataspine provides the best-in-class tools, elastic infrastructure and consistent workflows for every stage of the lifecycle

Powerful and flexible dev environments

Explore data and build models using Jupyter and Zeppelin notebooks. Use open source frameworks without setup, scale the underlying hardware in clicks, visualize and scale experiments from laptop to clusters -- all from a simple, self-serve interface.

Elastic infrastructure for all your ML workloads,
powered by Kubernetes

Focus on what matters without worrying about underlying infrastructure. Use on your cloud of choice or bare-metal, leverage multiple CPUs or GPUs, or run workloads in parallel while we take care of all provisioning and scaling. Only pay for what you use.

One-click production deployment, monitoring & scaling

Productionize models directly from notebooks or CLI as containerized microservices & REST API endpoints. Monitor performance metrics in real-time, A/B test and optimize safely in production. Deploy on any public cloud, VPC or on-premise.

Single point of control for management & ops

Manage models and infrastructure in simple workflows. Forget countless dependencies and maintenance overheads for your stack. Seamlessly use industry standard open-source tools & frameworks, or integrate with existing pipelines.

Supported frameworks & integrations

Infrastructure agnostic, framework agnostic, Language agnostic

Dataspine runs on hybrid, on-premise and leading public clouds, without the lock-in. We support popular frameworks including TensorFlow, Keras, PyTorch, Scikit-learn, XGBoost and Spark.

Production workflows (preview)

Managed services such as continous training and deployment pipelines, version control with git and docker, A/B testing, monitoring steamline your prod lifecycle and do all the heavy lifting.

Greater control, flexibility and reproducibility

Keep full control of your data and models. Enjoy flexibility in infrastructure, tools and pricing without compromising on quality. Do more with less head count.

Why Dataspine?

Simple, Customizable, Scalable, and Cutting Edge

The process of building and deploying neural nets and data pipelines that are mission critical can be immensely complex. Dataspine takes away the complexity of building your in-house machine learning setup, and simplifies the workflow so you can focus on what matters.

Our mission is to enable organizations of all kinds and sizes to solve business problems using machine intelligence.