The Most Intelligent Brain


Discover Our Technology

To unlock the latent value in an ever-increasing array of datasets,’s AI platform represents an engine with unique components to support optimal and efficient decision-making. curates and enhances a valuable data lake for insights generation and leverages advanced feature extraction algorithms to understand the characteristics that are critical for value creation.

Any brain has 5 pillars to transform data into actionable insights.

Extract & Connect

  • has a distinct capability to capture data scattered across the private and public domain, which is collated into a curated data lake: Main sources are client data, public data and 3rd party data.
  • Those data sources can be transformed into usable data and are regularly updated with dynamically refreshing data which might impact outcomes.
  •’s custom-built NLP technologies extract structured and unstructured text to detect relevant information
  •’s proprietary NLP engine can normalise medical terminology, detecting mentions of medical concepts in the text and linking them to medical ontologies and structuring the information into topics for enrichment


  • The connected data is enriched through feature extraction algorithms that identify and categorise the data to amplify the key drivers and changes in behaviours in the data
  • Automated self-learning that places more emphasis on recent changes in the behaviours of the actors within the pharmaceutical ecosystem and provides robust and continuous AI training. 
  • After noise removal, key drivers are shaped and get adjusted according to the time weight and take dynamic scoring for input. 
  • Feature extraction transforms the data into a standardised, manageable resource that can be correctly used for modelling.


  • predictions are delivered via robust, validated trained models, rather than rules-based systems. This is to maximise prediction accuracy and helps recognize the patterns and trends over time
  • The brain, recommends actions and insights that are generated based on robust modelling, with explanations and reasons provided to explain the outputs, instilling trust in users 
  • The prediction models feed the enriched data into specialist algorithms to produce predicted outcomes
  • Prediction models build on the enriched data which allows more accurate and precise predictions to be made, based on the behaviours of actors


  • brains recommend actions, highlighting what can be done now based on the predictions from the prediction engine 
  • The unique actionability model provides dynamic and meaningful insights across the business
  • Actionability involves training the AI brain to identify the best course of action that can be meaningfully implemented to drive the desired outcome
  • The engine runs several simulations and evaluates if those recommendations are actionable or not and creates the final actionable suggestions.


  • brains explain each actionable recommendation to evidence why it is recommended. 
  •’s explainability model provides traceable and transparent reasoning behind each output. 
  • Using a unique causality module to identify hidden variables to provide explanations for outcomes that go beyond standard correlation-based modelling.
  • Using the explainability model, translates key drivers into a language that can be easily understood, providing the evidence to drive and support the recommended actions.

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