Engine layer
Learn from behavior. Act. Record the outcome. Repeat.
Behaviors turns raw activity into a self-improving loop. The engine mines patterns, recommends the next best action, records the decision and its outcome as first-class items, and recalibrates — so the system gets sharper the more it's used.
lattice.mine · learning.recordDecision / recordOutcome
What you get
Patterns without rules
Emergent behaviors surface from activity — no hand-authored rules to maintain.
Decision → outcome loop
Decisions and outcomes are first-class, so credit is assigned and the model self-corrects.
Sharper over time
Every recorded outcome feeds back into the next recommendation.
How it works
The loop, three calls.
- STEP 01
Mine
The engine mines behavior into emergent patterns.
- STEP 02
Recommend
It surfaces the next best action for a subject.
- STEP 03
Record & learn
Log the decision and its outcome; the loop recalibrates.
lattice.mine→learning.recordDecision / recordOutcomeFeatures
Pattern mining
Emergent behaviors surface from activity without hand-authored rules.
Decision → outcome loop
Decisions and outcomes are first-class, so credit is assigned and the model self-corrects.
Recalibrates continuously
Every recorded outcome feeds back into the next prediction.
FAQ
Questions, answered.
Do I have to write rules?+
No. Behaviors are mined from activity rather than hand-authored, then refined by the decision→outcome loop.
More engine layers
Memory
Recall that compounds.
Cross-session persistent memory with hybrid search and a knowledge graph. The engine decides what's worth keeping, so context carries between conversations without bloating your prompts.
memory.observe · memory.search · memory.reflect
Predictions
Foresight, not just recall.
Declare any target and the engine predicts it from a subject's history — calibrated, provenanced, and abstaining when the signal is thin. This is the layer mem0 and MemoryLake have no answer for.
lattice.predict (event · numeric · time · anomaly)
From patterns to next-best-action.
The engine mines behavior into emergent patterns and closes the loop: predict, let the agent act, record the outcome, and watch the patterns recalibrate. Decisions and outcomes are first-class.