The cognitive core extracted from ZenAI — tested, proven, open source. 9 foundational algorithms that teach your AI to remember, forget, and sleep.
ZenBrain is not an experiment. It's the open-source memory core behind ZenAI — our AI operating system with 11,589 tests and 7 cognitive pillars. We extracted the memory algorithms so you can use them.
ZenBrain comprises 15 neuroscience-grounded algorithms: 9 foundational mechanisms — FSRS, Hebbian, Sleep Consolidation, Bayesian Confidence, and others — open-source as @zensation/algorithms (zero dependencies); plus 6 Predictive Memory Architecture (PMA) components that govern memory dynamics and run in the production system: NeuromodulatorEngine, ReconsolidationEngine, TripleCopyMemory, PriorityMap, StabilityProtector, MetacognitiveMonitor.
Strengthen connections through co-activation
Hebb 1949Optimal review scheduling
Wozniak 2022Memory replay during sleep — like the brain
Stickgold & Walker 2013Forgetting curve with adaptive intervals
Ebbinghaus 1885Belief updates with prior + evidence
Bayes 1763Emotional markers for better recall
Damasio 1994Associative network activation
Collins & Loftus 1975Time-based memory encoding
Howard & Kahana 2002STM→LTM transfer with importance scoring
McClelland et al. 199595% CI for all probabilistic outputs
Wilson 1927Share knowledge across contexts
Tulving 1972Export Ebbinghaus curves as data points
Ebbinghaus 1885Dopamine, NE, 5-HT, ACh — four channels with tonic + phasic dynamics
Schultz 1997 · Aston-Jones 2005Memory becomes labile on retrieval — four PE-gated update modes with rollback
Nader 2000 · Schiller 2010Three traces with divergent dynamics — fast (4h), medium (14d), deep (logarithmic)
Squire & Bayley 2007The MemoryCoordinator orchestrates all layers — from Working Memory to Sleep Consolidation. One call. The system decides.
import { MemoryCoordinator }
from '@zensation/core';
const memory =
new MemoryCoordinator();
// Store — auto-routes
await memory.store(
'TypeScript has generics',
{ context: 'learning' }
);
// Recall — cross-layer
const results =
await memory.recall(
'What do I know about TypeScript?'
);
// Sleep — consolidate
await memory.consolidate();No setup. No config. No account.
npm install @zensation/algorithms
npm install @zensation/coreimport { MemoryCoordinator } from '@zensation/core';
import { HebbianLearning, FSRS } from '@zensation/algorithms';
const memory = new MemoryCoordinator({
algorithms: [HebbianLearning, FSRS]
});
await memory.store('Project deadline is Friday',
{ context: 'work' });
const recall = await memory.recall(
'When is the deadline?'
);
console.log(recall);{
"content": "Project deadline is Friday",
"confidence": 0.94,
"layer": "short-term",
"decay": 0.87,
"nextReview": "2026-03-28T09:00:00Z"
}@zensation/algorithms is the pure core — zero dependencies. @zensation/core orchestrates everything with the MemoryCoordinator.
npm i @zensation/corenpm i @zensation/algorithms# published with v0.3# published with v0.3Apache 2.0. Contributions welcome. No CLA required.
Source code, issues, discussions
Repository →Questions, ideas, show & tell, release updates
Join →Read CONTRIBUTING.md, pick an issue, open a PR
Read guide →MemoryCoordinator, Sleep Consolidation, 276 tests
March 2026@zensation/mcp-server — IDE integration (Cursor, VS Code, Claude)
H2 2026LOCOMO benchmark vs. Mem0/Zep/LangMem
H2 2026API stability, ZenBrain Cloud MVP
Q3 2026ZenBrain is the extracted, open-source core of the memory algorithms. ZenAI is the complete AI operating system built on ZenBrain. Want to build your own system → ZenBrain. Want the finished product → ZenAI.
No. @zensation/algorithms is zero-dependency and runs completely in-memory. Optional persistence adapters — adapter-postgres (pgvector) and adapter-sqlite (zero-config) — are in preview and will be published on npm in v0.3.
ZenBrain is LLM-agnostic. The algorithms work on embeddings — whether from OpenAI, Anthropic, Mistral, Ollama, or your own model.
The algorithms come from ZenAI (348K LOC, 11,589 tests, months in production). The extracted package has 276 of its own tests. API stability (Semver 1.0) is planned for Q3 2026.
Mem0 has 2 memory layers and focuses on cloud API. ZenBrain has 7 layers, Sleep Consolidation, FSRS, Hebbian Learning, Confidence Intervals — all self-hosted, zero dependencies, TypeScript-native.
Yes. The algorithms package is completely standalone with zero dependencies. You can import individual algorithms and integrate them into existing systems without using the MemoryCoordinator.