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What do you do with the data now you have it?
We specialise in training Artificial Intelligence
models for very specific business problems.
Sometimes those models are unsupervised - they uncover patterns and relationships in datasets that humans simply could never see.
Other models are supervised in their learning - we train them to understand and learn from historic data so they can predict and forecast.
Language is the major
data type for human intelligence
From emails & handwritten notes,
to conversations on calls and product reviews on YouTube - language is the main way of sending data between people.
nlp
We are leaders in Natural Language Processing - a family of models and algorithms that make sense of language - from understanding topics and themes, to predicting emotion and the feelings of the people behind the words- we’ve developed models that have helped clients understand pain points inside their organisations, to understand the interests and what matters to their customers
Advanced
Market Research Methods
Being able to use market research, alongside AI and machine learning, means that we can answer very specific questions; questions that make a big difference - like understanding the order of preferences, or knowing who to talk to next, or being able to make sense of
We don't just stick to AI
We use robust scientific methods like Structural Equation Modelling, Maximum Differential Analysis, Sequence Analysis and Network Science techniques to make sense
of the data at hand.
Predictive Analytics
Prediction isn't always about the future - sometimes it’s about predicting what happened, or even what is current, what someone’s main interests are, what a customer’s best product might be.
We use supervised learning models to uncover the secrets that move business forward.
From forecasting who is likely to churn, to which products are likely to sell out, or not sell at all.
By training custom models on unique data we’re able to develop the most accurate predictions and forecasts in the market.
clustering
Our clustering seeks to find the most meaningful lines of separation - and produce segments that are more meaningful to your business. This might mean that customers are grouped together in seemingly illogical ways - in fact there is something more important linking them together - and this linking is what makes the difference
Typical segmentation draws distinctions based on obvious lines.
We use a variety of unsupervised models and methods to let the data speak for itself and find patterns and connections that otherwise would be missed.