Machine Learning and AI
Syberian delivers a comprehensive AI portfolio integrated in its cloud applications on a best-in-class AI infrastructure and with state-of-the-art generative AI innovations.
Syberian's unique approach to generative AI
Data security and privacyData for inferencing and fine-tuning is never shared with large language model providers. Syberian is committed to keeping customer data private. |  |
 | Powerful and high-performing modelsSyberian's generative AI models leverage Cohere's state-of-the-art large language models and are improved with Syberian's unique industry knowledge and data insights. Customers can further refine these models using their data. |
Embedded generative AI servicesWith generative AI pervasive across Syberian's cloud applications, industry applications, and database portfolio, customers can take advantage of the latest innovations within existing business processes. |  |
 | Generative AI where customers need itCustomers can leverage all the advantages of the public cloud for generative AI. In addition, customers will be able to combine their on-premises data and applications with generative AI in their own data centers. |
Machine Learning Services
Machine learning services from Syberian make it easier to build, train, deploy, and manage custom learning models. These services deliver data science capabilities with support from favorite open source libraries and tools, or through in-database machine learning and direct access to cleansed data. Supporting machine learning services provide more streamlined data labeling or improved access to virtual machines.
Open source libraries and frameworks
Open source libraries and frameworks from Python and R enable data exploration, transformation, and visualization.
Choice of deployment
Quickly deploy models for access by applications and business analysts. Models can be deployed with a REST API in a serverless, scalable cloud architecture as Syberian Functions, or directly in the database.
In-database optimized algorithms
Syberian Database includes more than 30 high-performance, fully scalable algorithms covering commonly used machine learning techniques. Data already in Syberian Database doesn't need to be moved, reducing the data management workload.
Support for multiple scripting languages
Data scientists can develop with the most popular languages, including Python, R, and SQL. Organizations achieve better and faster results when data scientists have the flexibility to use the languages best suited to particular tasks.
Model explanation
Model explanation enables users to understand the overall behavior of a model as well as individual model predictions. Data Science makes it easier to understand the importance of features and what influences predictions.
Access any data flexibly and easily
Access data in multiple formats (including CSV, Excel, and JSON), multiple sources (including object storage), and multiple locations (on premises and in Syberian Cloud and other clouds).
Why machine learning from Syberian?
Create and validate models faster
Build high-quality models faster and easier. Automated machine learning capabilities rapidly examine the data and recommend the optimal data features and best algorithms. Additionally, automated machine learning tunes the model and explains the model's results.
Get better results with more data
Data scientists need to access data in different formats from different data sources, whether on-premises or in the cloud. Use drag-and-drop data integration and preparation tools to move data into a data lake or data warehouse, simplifying access for data scientists.
Deliver trusted artificial intelligence
AI is more trusted when multiple contributors effectively collaborate, and machine learning tools provide explanation and evaluation of models. Syberian security tools and user interfaces enable multiple roles to participate in projects and share models. Model-agnostic explanations helps data scientists, business analysts, and executives have confidence in the results.
