Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
STOCHOS is an advanced probabilistic AI solution designed specifically for engineering and research and development applications. It harnesses existing simulation, testing, and measurement data to swiftly predict new variants while providing uncertainty assessments for each prediction, allowing engineers to discern when to trust the results or opt for traditional solvers. Utilizing the DIM-GP framework, STOCHOS is effective even with limited datasets, ranging from just a few dozen to a few hundred samples, and can handle various data types such as scalars, signals, 2D and 3D fields, meshes, geometries, and images. Its capabilities include surrogate modeling, uncertainty quantification, Bayesian and multi-objective optimization, as well as multi-fidelity modeling and sensitivity analysis, along with generative geometry techniques. STOCHOS Flow, a user-friendly visual workbench, enables the creation of workflows without the need for coding, allowing teams to deploy them as web applications. The software operates on local hardware and can be installed offline, ensuring accessibility and privacy. Founded in 2018 in Grafing bei München, PI Probaligence is part of the CADFEM Group and has established itself as a technology partner with Ansys, promoting innovative solutions in engineering. Furthermore, its ability to integrate seamlessly into existing processes enhances productivity and drives efficiency in engineering teams.
Description
Select the necessary configuration and resources for particular code segments in your ongoing project, as it only takes a few seconds to implement changes in a training scenario and secure the results. Opt for the appropriate setup for computational resources to initiate model training in mere seconds, allowing everything to be generated automatically without the hassle of infrastructure management. You can choose between serverless or dedicated operating modes, and efficiently manage project data, saving it to datasets while establishing connections to databases, object storage, or other repositories, all from a single interface. Collaborate with teammates globally to develop a machine learning model, share the project, and allocate budgets for teams throughout your organization. Launch your machine learning initiatives in minutes without requiring developer assistance, and conduct experiments that enable the simultaneous release of various model versions. This streamlined approach fosters innovation and enhances collaboration among team members, ensuring that everyone is on the same page.
API Access
Has API
No
API Access
Has API
Yes
Screenshots View All
No images available
Integrations
Jupyter Notebook
No
PyTorch
No
TensorFlow
No
Yandex Cloud
No
Yandex Data Proc
No
YandexGPT
No
Integrations
Jupyter Notebook
Yes
PyTorch
Yes
TensorFlow
Yes
Yandex Cloud
Yes
Yandex Data Proc
Yes
YandexGPT
Yes
Pricing Details
Quote on request
Free Trial
No
Free Version
No
Pricing Details
$0.095437 per GB
Free Trial
Yes
Free Version
Yes
Deployment
Web-Based
No
On-Premises
Yes
iPhone App
No
iPad App
No
Android App
No
Windows
Yes
Mac
No
Linux
Yes
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
Yes
iPad App
No
Android App
Yes
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
Yes
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
Yes
In Person
Yes
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
Yes
In Person
No
Vendor Details
Company Name
PI Probaligence GmbH
Founded
2018
Country
Germany
Website
probaligence.com
Vendor Details
Company Name
Yandex.Cloud
Founded
1997
Country
Russia
Website
cloud.yandex.com/en/services/datasphere
Product Features
Machine Learning
Deep Learning
No
ML Algorithm Library
No
Model Training
No
Natural Language Processing (NLP)
No
Predictive Modeling
No
Statistical / Mathematical Tools
No
Templates
No
Visualization
No
Product Features
Machine Learning
Deep Learning
No
ML Algorithm Library
No
Model Training
No
Natural Language Processing (NLP)
No
Predictive Modeling
No
Statistical / Mathematical Tools
No
Templates
No
Visualization
No