Quintary AI
integrating machine learning approaches such as artificial neural networks with semantic models on the basis of a universal formal description
The Explainable A.I. Company
About the Company
The main goal of our company is to create Explainable AI systems that consists of compatible interoperable intelligent systems connected into the cloud with the Technology core. The Technology Core includes up-to-date versions of all components used by the interconnected systems. Semantic compatibility of the systems allows automatic maintenance of the components, so that every system has access to the most stable version of the underlying platform and all required components at all times.
The basic ideas of our approach are:
Integration of machine learning approaches such as artificial neural networks with semantic models on the basis of a universal formal description
Information security:
All changes are automatically verified
Private information is stored on the owner's server
No changes can be made without logging
Scheduled binary and human-readable dumps
Each system may share a part of stored information to become a reliable source of information in some subject domain. This way, a complex problem can be solved by utilizing information from several systems
Technology
In order to design semantically compatible computer systems, we use our Knowledge Graph Technology.
At the heart of this technology is SC-code – a standard for semantic representation of information that is based on set theory and graph theory.
The unique feature of SC-code is that this language consists of only 5 elements. SC-code is powerful enough to formally represent and process all kinds of information from any subject domain, including logical statements, programs, and metastructures of any complexity.
SC-code features:
As a result:
Semantic and syntactic compatibility of knowledge represented in SC-code
Used Technologies
Why should you choose us?
Quintary AI allows your company to find meaning in its data and improve the quality of business decisions. Using a common platform, IT and business users can work together to create a data-driven organization:
Enterprise security and scalability to meet your standards of reliability, confidentiality and compliance
System workflows help teams to collaborate
Cloud-based architecture ensures direct access to shared information for all interconnected systems
With us you can trust your data and develop new ideas
Identifying all the data used within the system can help you analyze information flows and set key priorities for growth. It also enables us to create basic individualized structures that allow the system to expand independently according to the specifications and integrate increasingly complex data. This way, you use the system to its full potential.
Using our product, you can consolidate data between systems by providing universal definitions to ensure that users build upon the same foundation.
Our system sets priorities and simplifies approval, usage, and data storage policies to give analysts access to all data that they are authorized to see.
An analysis will result in valid conclusions only if the data is reliable and full transparency of the origin of the data is ensured. This is the core principle of our system. Interaction between multiple intelligent agents will provide powerful analytic capabilities to help you get the insights you need to gain a competitive advantage. Quintary AI guarantees access to reliable data records, with info on context and origin of that data ready to be utilized as necessary.
In most cases, extending the functionality of systems developed using our approach comes down to expanding the knowledge base, which can be carried out automatically or with minimal developer involvement. Moreover, competence requirements for such developers are much lower than in the case of a traditional systems developer.
Plans
Our ecosystem is a limitlessly expandable group of constantly developing intelligent systems that:
interact with each other, with users of intelligent systems, and with traditional computer systems to solve complex problems cooperatively;
constantly maintain a high level of compatibility and mutual understanding in interaction both among themselves and with users.
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