The Science Behind Our Work

Augmenting human intelligence and execution
Analytics with Artificial Intelligence

CIF is a SaaS AI analytics cloud service based on symbolic logic and propositional calculus. In a nutshell, the AI part of the analysis is to read articles and documents like a human researcher and bring out important points and aspects. Our AI presents these important points and aspects in a visual map that enables a user to discover insights they might not have otherwise seen.


The Science Behind Our Work

With the advent of Internet, information is abundantly available and so is business intelligence. However, there is a general lack of science and technology to enable us in getting the gist of this information. Text in natural language is unstructured. Unstructured textual analytics is not new, but progress in this area is slow. Processing natural language for the purpose of finding gist in corpus requires software development on relate science. Many prevailing technologies relies on statistical science to perform machine learning on corpus, and then plug the results into neural network to support the Boltzmann Machine or Restricted Boltzmann Machine. The downside to this approach is domain dependency. For every vertical domain, it will require its own training dataset and neural network. This makes the approach not scalable.

Data science enables us to learn by observing data behavior. Machine learning is a popular technique used to discover how common data patterns relate to common outcomes. This enables data scientists to predict outcomes with present data – a strategic benefit driving the adoption of machine learning across many enterprises. This approach, however, has limitations; machine learning can only learn from the past. Humans are dynamic; change is constant. Machine learning models trained and tested for accuracy against historical data don’t know what to do when faced with zero-day scenarios – new variables, unknown outcomes. When an application works with human behavior, the AI must account for human rationale. If presented with a conference dialogue or transcript, the application must understand context, POV, and rationale based on the situation.

In recent years, many analytical solutions and tools have focused on quantitative data to navigate and extract insights. Quantitative data, however, is only a measure of human behavior, not rationale. For example, ‘Same Store Sales’ is a metric often used in the retail industry. Machine learning models may recognize a decline, but will miss the underlying reasons driving that change – critical insights for executives managing a turnaround or competitors looking for a weakness to exploit. Identifying and understanding the root-cause is critical to successful business execution. The value of rationale analysis is just as important - if not more - than quantitative analysis in the formulation of tactical strategy.

SiteFocus is in a mission of developing automated software solution for machine to understand the rationale behind corpus across different industries and topics without separate machine learning effort. To do that, we focus our work in the area of propositional calculus, symbolic logic, science of rationale and context discriminant with machine learning. This enable us to express subjects and rationale using a supporting fact model. The supporting fact model is then expressed visually in an interactive Meta-Vision display where users can examine each subject according to its connotation, supporting facts and draw insights.

Understanding the Technology

CIF is a SaaS AI analytics cloud service based on symbolic logic and propositional calculus. In a nutshell, the AI part of the analysis is to read articles and documents like a human researcher and bring out important points and aspects. Our AI presents these important points and aspects in a visual map that enables a user to discover insights they might not have otherwise seen.

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Meta-Vision Case Study
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Natural Language Understanding in Fraud Risk Management - a case study
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What impact can natural language AI have for financial services? Plenty. This blog discusses the impact of applying our NLU AI approach to IPO prospectus, demonstrating the versatility and range of insight of the CIF AI system.


Where machine learning stops, see how autonomous learning & Symbolic AI take you further with immediate results & time to value


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