machine learning

we deliver reliable & accurate predictors to translate complex decision making into straightforward results for action.

how we do machine learning









natural language processing (NLP)

using language & audience specific behavior flows, we can predict, classify & interact with your users & documentation systems to automate day-to-day tasks.

implemented NLP use cases:

  • speech recognition
  • AI chatbots
  • data mining analysis
  • clinical documentation meta analysis
  • clinical decision & study support
  • computational phenotyping
  • prior authorization

computer vision (CV)

combining accurate classification within both image & video content, we can analyze physical & virtual environments to provide real-time decision making.

implemented CV use cases:

  • image classification
  • object detection
  • segmatic segmentation
  • instance segmentation
  • panoptic segmentation
  • person segmentation
  • object reconstruction

recurrent & convolutional neural networks
(RNN's & CNN's)

if you need to discover the features of your decision making or deal with overtly complex data models (e.g. weather or human behavior) we can engineer “deep learning” & “artificial neural network” models to produce a continuously improving prediction.

implemented RNN/CNN use cases:

  • machine translation
  • image classification
  • speech recognition
  • video tagging
  • generative models
  • regression prediction

predictive analytics (PA)

if your decision making can be quantified into known parameters we can engineer “supervised” & “unsupervised” machine learning models with statistical analysis to produce reliable and accurate results.

implemented PA use cases:

  • asset management & tracking
  • document & contract processing
  • ETA algorithms
  • health & community risk analysis
  • price & stock forecasting
  • health & community risk analysis

a few of our machine learning releases

ready to see what we can do with your machine learning idea?