There’s been a lot of buzz as these technologies have entered the market. We use AI and ML to create data-driven, automated predictive modeling that offers the most sophisticated insights to clients struggling to activate large data sets.

When you want people to truly envision a future state or a particular environment, what better way than to put them there? VR and AR offer surprisingly effective methods of tapping into the senses to offer a more holistic picture of the human experience.

Unlike traditional models that imagine people are separate, independent actors, agent-based modeling creates simulated markets with parameters around realistic social processes. This often results in emergent properties that are surprising and non-intuitive.

By ingesting and interpreting natural human language, we’re able to identify what people are talking about at scale. Applications for clients include open-ended coding, sentiment analysis, and entity detection.

Using machine learning, we can transform customer data using deep neural networks and signal detection, then apply predictive modeling to large databases. Our models extrapolate from several thousand contacts to tag and assign a propensity score to customer segments across a database of millions of customers.

Using passive metering, survey response, and appended, anonymized streams of third-party data, we can open category-specific streams of data to build insights around real-time customer behavior.