Dagger points you to hot, relevant, privileged, or issue-specific documents using supervised and unsupervised machine-learning techniques that are continuously updated to keep in the vanguard of artificial-intelligence technology, including natural language processing, continuous active learning, dynamic tuning of parameters, algorithm selection, and feature representations, and cross-validation techniques to maximize training value and accuracy assessment and minimize review burden.
Dagger’s predictive analytics outputs can be overlaid into your existing review tool (e.g., Relativity, Concordance), or you can use ours.