Strange LabFROM EVIDENCE TO LEARNED DYNAMICS
Raw data tells us what happened.
A model learns how things change.
The event stream connects the two: source material becomes a history that can be inspected, represented, and learned from.
SIX STAGES · SELECT A STAGE TO FOLLOW THE HANDOFF
↳Useful before trainingThe event stream also feeds company knowledge, search, workflow discovery, and evidence inspection directly.
WHAT PASSES TO THE NEXT STAGE
WHY IT MATTERS
IMPLEMENTATION REFERENCE
THE DATA YOU CAN EXPLORE NOW
What the final model contains
A trained encoder turns available history into a compact state. A predictor estimates change in that state. Fitted readout heads translate it into specific questions: outcomes, unusual changes, or action-conditioned next states.
See the research and model comparisons. The deliverable is a model bundle with its feature definitions, preprocessing, time splits, checkpoints, and evaluation evidence—not just a weights file.