With high-definition monitoring, cloud-based storage, and advanced machine learning, Envision facilitates scalable real-time behavioral monitoring of individual animals in their group-housed home cage environment. The novel open architecture of Envision allows end users to leverage pre-defined digital measures as well as easily develop their own custom measures, providing near-unlimited flexibility and continuous evolution of tools to classify animal behavior.
With Envision Developer Environment, users can leverage the core framework of Envision to create custom digital measures. In combination with JAX validated digital measures the opportunities to tailor Envision to your specific research needs are nearly limitless.
A - See study overviews or view group specific data.
B - Review acclimation and dosing records.
C - Filter by activity to track and manage study variables.
A - Quickly view cage and individual level activity.
B - Review annotation to ensure welfare and treatment compliance.
C - Insights on animal behavior and physiology for any day and time.
D - Click on charts to display video to better understand metrics.
E - Add annotations to highlight unusual behavior or mark significant events such as cage changes or study interventions.
A - Export and extrapolated digital measures for further statistical analysis.
B - Compare treatment groups and identify outliers in study data.
This product sheet explains the data, machine learning, and end-to-end validation framework behind Envision, showing how continuous home-cage monitoring delivers robust, reproducible insights into animal biology.
Learn how the Behavioral Phenotyping Core at Seattle Children’s Research Institute expanded its capabilities with the integration of the Allentown Discovery IVC Rack powered by The Jackson Laboratory.