Skytree, Inc.
Headquarters Address
1731 Technology Drive Suite 700
San Jose, California 95110
United States
Primary Contact:
Dylan Steeg
Phone: +1 408-392-9300 x1004
Tier 1
Skytree, Inc.

Skytree Infinity is the leading enterprise machine learning platform for big data, built from the ground up for big data to scale to the largest and most diverse data sets. Skytree’s unified platform is easy to use and delivers enterprise class features, including unparalleled model governance, and patent-pending features to increase the productivity of data scientists.

Skytree’s purpose built big data architecture, enter-prise class features, and ease of adoption delivers the most accurate and fully documented models in less time, resulting in better insights, governance and business results.

Skytree delivers a unified machine learning platform, including data preparation, model building and deployment. Skytree provides a diverse set of envi-ronments for data scientists, so they can build mod-els in the language that they are most familiar with, whether that be Java, Python or the Skytree Com-mand Line Interface (CLI). Skytree also provides a powerful, easy to use, project oriented Graphical User interface (GUI) for both highly sophisticated data scientists as well as data analysts.

Skytree’s project based environment allows data scientist to efficiently and effectively manage their projects, datasets and models. Data scientists can organize their work in Skytree’s intuitive project dashboard, providing an easy to understand over-view of all projects, activities and progress.

Skytree Infinity allows data scientists to easily navigate through datasets, providing graphical views of datasets through tables and charts so data scientist can quickly visualize and understand the data. Data scientists even have access to a wide array of com-mon machine learning transformations, as well as the ability to create custom transformations.

Skytree is built from the ground up for speed and scalability, which is critical for machine learning on big data. With Skytree, data scien-tists can build more models with more data, more features and run more experiments as a direct result of the platform’s superior speed and scalability.  The net results are more productive data scientists and more accurate models, providing greater business agility and driving better business results.

Skytree’s speed and scalability come from four core principles, which we call TrueScale™: 1) Design algorithms for speed and scalability, 2) Co-locate analytics on data nodes to reduce latency and increase speed even further, 3) Use in-memory processing, and 4) Use the latest High Performance Computing (HPC) techniques, such as reducing inter-node communication for near linear scalabil-ity. Whether you are deploying Skytree on one node or thousands of nodes, Skytree will always deliver maximum performance.

Since big data isn’t just about data volume, Skytree isn’t either. Sky-tree supports a wide variety of data, including structured, unstruc-tured text, log files, and time series data. Skytree is certified on Big Data, including Cloudera, Hortonworks, MapR, Spark and YARN.

Skytree Infinity takes model management to a new level with self-documenting models. Skytree provides visual documentation, which logs every dataset used, data split done, transformation per-formed, algorithm run, and result obtained for each and every model built with Skytree. The level of granularity takes model governance to new levels.

Skytree Infinity is the leading enterprise machine learning platform for big data, built from the ground up for big data to scale to the largest and most diverse data sets. Skytree’s unified platform is easy to use and delivers enterprise class features, including unparalleled model governance, and patent-pending features to increase the productivity of data scientists.

Skytree’s purpose built big data architecture, enter-prise class features, and ease of adoption delivers the most accurate and fully documented models in less time, resulting in better insights, governance and business results.

Skytree delivers a unified machine learning platform, including data preparation, model building and deployment. Skytree provides a diverse set of envi-ronments for data scientists, so they can build mod-els in the language that they are most familiar with, whether that be Java, Python or the Skytree Com-mand Line Interface (CLI). Skytree also provides a powerful, easy to use, project oriented Graphical User interface (GUI) for both highly sophisticated data scientists as well as data analysts.

Skytree’s project based environment allows data scientist to efficiently and effectively manage their projects, datasets and models. Data scientists can organize their work in Skytree’s intuitive project dashboard, providing an easy to understand over-view of all projects, activities and progress.

Skytree Infinity allows data scientists to easily navigate through datasets, providing graphical views of datasets through tables and charts so data scientist can quickly visualize and understand the data. Data scientists even have access to a wide array of com-mon machine learning transformations, as well as the ability to create custom transformations.

Skytree is built from the ground up for speed and scalability, which is critical for machine learning on big data. With Skytree, data scien-tists can build more models with more data, more features and run more experiments as a direct result of the platform’s superior speed and scalability.  The net results are more productive data scientists and more accurate models, providing greater business agility and driving better business results.

Skytree’s speed and scalability come from four core principles, which we call TrueScale™: 1) Design algorithms for speed and scalability, 2) Co-locate analytics on data nodes to reduce latency and increase speed even further, 3) Use in-memory processing, and 4) Use the latest High Performance Computing (HPC) techniques, such as reducing inter-node communication for near linear scalabil-ity. Whether you are deploying Skytree on one node or thousands of nodes, Skytree will always deliver maximum performance.

Since big data isn’t just about data volume, Skytree isn’t either. Sky-tree supports a wide variety of data, including structured, unstruc-tured text, log files, and time series data. Skytree is certified on Big Data, including Cloudera, Hortonworks, MapR, Spark and YARN.

Skytree Infinity takes model management to a new level with self-documenting models. Skytree provides visual documentation, which logs every dataset used, data split done, transformation per-formed, algorithm run, and result obtained for each and every model built with Skytree. The level of granularity takes model governance to new levels.