Observed arrival · 2026-09-18
AI-SEM, a visual structural-equation modeling workbench
A browser and desktop tool for building and comparing PLS-SEM and CB-SEM models on one visual canvas.
- For
- Researchers running structural equation modeling studies
- Worth noticing
- It compares SEM path coefficients with variable-importance scores from four named machine-learning libraries.
Field notes
The workflow starts with a visual measurement and structural model, then offers either Partial Least Squares or Covariance-Based estimation without requiring a second tool. Its AI Lab is described as handling literature-grounded construct discovery, synthetic survey data for pilot testing, and editable model suggestions. The page also exposes power-analysis controls and a cross-check against importance scores from XGBoost, LightGBM, CatBoost, and Random Forest. Desktop packages and a browser demo are both listed.
Observed signals
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Editorial observations of this landing page, not a rating.
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