Implementing next-generation ideas

The SAFEST is a probabilistic risk assessment toolchain that is fully automatic, scalable, and state-of-the-art. It is based on dynamic fault trees (DFT) and event trees and, thus, can faithfully assess the risk of fail-operational/fault-tolerant dynamic systems with decision-making capabilities. It is equally competitive with existing commercial tools (for static fault trees analysis), but offers more flexible modeling and analyses, going beyond the capabilities of other tools, of dynamic systems as it covers all DFT gates.

In large organisations where numerous teams work on separate PRA projects and exchange fault tree and event tree data, parameters, etc., the SAFEST enterprise version offers greater flexibility and ease of use thanks to its user management and data sharing modules.

It is a graphical editor of JANI modeling language that allows to create and edit automata in a “what you see is what you get” style. The editor offers tools to add locations and insert edges between them using drag & drop gestures. An automaton also needs to specify edge guards, rates, transition probabilities, data variable assignments and similar expressions. To this end, the editor uses constants, variables, expressions and functions that can conveniently be defined through a separate declaration module. The system composition module allows to create networks of multiple automata. In these networks, automata can synchronize using synchronization vectors, allowing, for example, the send-action of one automaton to synchronise with the receive-action of another one. The raw Jani format specifies labels and rewards through transient (“stateless”) variables. While this is a very flexible modeling approach, it can be cumbersome in some cases. The GUI therefore additionally provides a module to declare labels and rewards in a more user-friendly way. Finally, users familiar with the Jani specification can still inspect and edit the JSON-based Jani code on a textual level.

Hazardhive is the most used risk assessment software that is based on the bowtie method. It enables you to easily create bowtie diagrams to assess risk. Hazardhive is unique in its ability to visualize complex risks in a way that is understandable, yet also allows for detailed risk-based improvement plans.

To assist clients stay ahead of the curve with the newest CV innovations, we develop deep learning architectures for a range of CV tasks, including object recognition, image classification, smart video analysis, and GANs.

We help machines comprehend and interpret human language as part of our machine learning development services. Our ML developers provide top-notch NLP solutions for chatbots, automatic text categorisation, sentiment analysis, speech recognition, translation, and more.

For data mining solutions, our machine learning development group creates unique machine learning algorithms that find correlations, trends, and anomalies in big datasets to provide insightful information. With our comprehensive suite of data management services, you may uncover new business opportunities and enable more informed decision-making.

We create both basic and sophisticated predictive models using machine learning and deep learning algorithms, allowing businesses to predict their business outcomes, such as asset maintenance, labour planning, churn analysis, competitive analysis, and risks.

Custom IPA solutions that combine the power of data, machine learning, and automation are part of our machine learning development services. By incorporating deductive analytics and prediction into RPA systems, we simplify intelligent automation for any process.