ZenBrain Playground

The neuroscience-inspired, 7-layer memory architecture for AI agents.

Your AI forgets everything after every conversation. ZenBrain fixes that — with the same mechanisms your brain uses: spaced repetition, Hebbian strengthening, sleep consolidation and exponential forgetting curves. Not a vector database with a wrapper. Actual neuroscience.

Every number below is computed live by the real, open library — npm i @zensation/algorithms — running in your browser. Nothing is faked.

The Forgetting Curve

Ebbinghaus (1885) · FSRS spaced repetition

A memory decays as R = e−t/S. Turn on spaced repetition and watch each review reset the curve — so retention stays high with a fraction of the storage.

Spaced repetition — review on days 3 · 8 · 16
With spaced repetition
Without any review

Hebbian Learning

“Neurons that fire together, wire together”

When two memories are recalled together, the edge between them strengthens (asymptotically toward a cap). Left idle, it decays — and is pruned when too weak.

Edge weight
1.00
Co-activations
0
Status
neutral

Sleep Consolidation

Stickgold & Walker (2013) · memory replay

During sleep the hippocampus replays recent memories — important and emotional ones are strengthened, weak connections are pruned. Press sleep and watch it happen.

Replays this cycle
Weak edges pruned

Calibrated Confidence

Bayesian confidence intervals

ZenBrain never returns a bare number. Every estimate carries a 95% confidence interval that narrows as evidence accumulates — few reviews mean honest, wide uncertainty.

Point estimate
95% confidence interval