Linguistic Inferencing AI Tool​


Our solution has been created in conjunction with work that has come out of the Texas University Language Laboratory and based on works by world renowned linguists and psychologists. Through the application of artificial intelligence, we have been able to create software that is able to infer a personality profile for people based on their usage of language.

From a historical perspective Artificial Intelligence programs have been focused on Cognitive Computing, Computer Vision, Machine Learning, Neural Networks and Deep Learning algorithms. Very little has been done to provide the Artificial Intelligence with insight into the human beings they are decoding.

This is where our approach differs from the marketplace at the moment. We are helping computers understand human language, enabling them to interpret and recognize, human language and speech Any area of your business that touches people or customers can be enhanced:

Machine Learning & AI: AI’s are able to understand people at an emotional level where they have previously used demographic and purchasing behaviour

Marketing and Communications: Marketing teams are able to more granular in their digital promotions to customers.

Fraud and Risk: Risk models are able to receive personality traits that are indicative of further investigation. Credit models have greater efficacy due to an increased number of data points

Return on investment: Reduced acquisition costs, revenue upticks and increase in marketing spend efficiency with the ability to outsell competitors who have not undertaken this strategic course.

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Use existing data to run machine learning on historic behavior and identify buying behaviors.


Profile customers, prospects or target data by matching them to their social media profiles and using linguistic inferencing to create 250 plus data points.


Sourcing prospects using social media and other data sources.


Optimize media budgets by removing low propensity audiences.


Dynamically generate large volumes of creative assets for ads.

Integrate audience segments into social media platforms. Serve ads based on segmentation. Updating records based on social media activity has defined a market segment which has previously been inaccessible, even when using traditional social adverts, which leads to improved growth opportunities.

Valuable to apply to target data to identify leads likely to be of higher value to client. Match leads to social media profiles to create highly targeted audiences with similar characteristics.

Automated ad creation to match targeted audiences, and machine learning on ad performance to eliminate lower performing ads and find characteristics of higher performing ads.

Cohesion and alignment: Evaluate the degree to which brands, people and customers are aligned, and signals that can indicate misalignment with customer groupings and messaging to the market. Mass customisation: Tailor the marketing message that has resonance with specific customer segments. Generate individualised messages in mass via digital and above the line channels.


By having a better understanding of the person that is presented to it is far easier to build report as well as negotiate a successful win-win outcome. Wouldn’t it be great to understand that the individual you are engaging with is very logical and detailed oriented as opposed to perhaps to perhaps mostly interested in the “bottom line” or alternatively relies on emotions to make decisions? Armed with this information conversations and presentations can be structured accordingly. Risk aversion: Evaluate risk aversion by analysis through understanding client’s behaviour through word usage.

There is also a use-case in call centres, to match the lead’s psychographic data with the most appropriate call centre operator, and also present the lead’s psychographic profile before or at the point the call starts, thereby resulting in improved communication.


Linguistic inferencing can be used to profile existing or potential employees.

Language psychology can be used to gain important predictive intelligence into the health of people, their behaviour, as well as behaviour triggers for employees or any group of people

We gain insight into authenticity and confidence. This analysis can be conducted at a point in time where on a question-by-question basis, identify when an individual is signalling discomfort with certain topics through linguistic signals that indicate a deviation from their norm related to stress, increased cognitive processing, lower authenticity, etc.


      Through linguistic inferencing profiling it is possible to augment existing credit vetting tools by inferring character traits of an individual and identifying risk.