Dataspine provides infrastructure and DevOps automation for machine intelligence
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.
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.
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.
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.
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.