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What is STOCHOS?

STOCHOS is a cutting-edge probabilistic AI tool tailored for engineering and research and development sectors. It efficiently utilizes available simulation, testing, and measurement data to quickly forecast new variants while offering uncertainty assessments for each outcome, enabling engineers to determine when they can rely on the findings or revert to conventional solvers. Using the DIM-GP framework, STOCHOS proves effective even with smaller datasets, accommodating samples ranging from a handful to several hundred, and is capable of managing diverse data types, including scalars, signals, 2D and 3D fields, meshes, geometries, and images. Among its features are surrogate modeling, uncertainty quantification, Bayesian and multi-objective optimization, as well as multi-fidelity modeling and sensitivity analysis, in addition to generative geometry techniques. The user-friendly STOCHOS Flow visual workbench allows users to build workflows without requiring programming skills, enabling teams to implement these workflows as web applications easily. The software can be installed on local hardware and works offline, thus ensuring both accessibility and privacy for users. Established in 2018 in Grafing bei München, PI Probaligence operates as part of the CADFEM Group and has emerged as a key technology partner with Ansys, fostering pioneering solutions in the engineering domain. Moreover, its seamless integration into existing workflows not only boosts productivity but also enhances operational efficiency within engineering teams, making it a valuable asset in today's fast-paced technological landscape.

What is GUMsim?

Measurements inevitably experience variations from their true values, a scenario referred to as measurement uncertainty, which is particularly relevant when evaluating or calibrating measurement instruments or methods. Accurately quantifying this uncertainty is crucial for maintaining quality control. GUMsim®, compliant with the most recent Guide to the Expression of Uncertainty in Measurement (GUM) and its supplement 1, employs advanced computational algorithms that support a more efficient assessment of measurement uncertainty in accordance with ISO/IEC 17025 standards. The assessment of measurement uncertainty relies on a mathematical framework and statistical evaluation of all factors that affect measurement results. To simplify this procedure, GUMsim offers an intuitive input interface suitable for various measurement models. Furthermore, it includes multiple pre-defined application models, which serve as templates designed to aid users in carrying out specific evaluations, facilitating the initiation of measurement uncertainty assessments. This aspect not only improves the overall user experience but also promotes uniformity in measurement practices across diverse applications, ultimately reinforcing the reliability of measurement results. As a result, users can approach their uncertainty evaluations with greater confidence and efficiency.

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Integrations Supported

Additional information not provided

Integrations Supported

Additional information not provided

API Availability

API Availability

Pricing Information

Quote on request

Pricing Information

€870 one-time payment

Supported Platforms

Windows
On-Prem
Linux

Supported Platforms

Windows

Customer Service / Support

Web-Based Support

Customer Service / Support

Standard Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub

Company Facts

Organization Name

PI Probaligence GmbH

Date Founded

2018

Company Location

Germany

Company Website

probaligence.com

Company Facts

Organization Name

QuoData

Company Location

Germany

Company Website

www.quodata.de/gumsim

Categories and Features

Machine Learning

Not specified

Categories and Features

Statistical Analysis

Statistical Simulation

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