Features
Self-supervised contrastive learning for time-series
Supervised embedding using auxiliary behavioral labels
Hybrid hypothesis- and discovery-driven modes
Consistency metrics for comparing latent spaces
k-nearest neighbor decoding from embeddings
Supports calcium imaging and electrophysiology data
Integration with DeepLabCut for pose embeddings
scikit-learn-compatible API
Built-in plotting with matplotlib and plotly
Time-series attribution maps (AISTATS 2025)
Multi-session and multi-animal data support
GPU-accelerated training via PyTorch
Docker container for reproducible analysis
Quick-Start Drafting for legal documents, clauses, emails, contracts
Comprehensive Document Analysis for insights and summarization
Contextual Legal Research across US federal and state law (50 states)
Medical Chronologies generation for personal injury cases
Medical Billing Summaries generation
Thought Partnership (AI as team member providing insights)
Secure closed model for data confidentiality
SOC 2 compliance certification
Enterprise admin controls and user management
Collaboration features for shared document sets
Priority support with account manager (Enterprise)
Multi-practice area support (PI, family, employment, criminal, corporate)
