Memory that thinks
Not a vector database. A cognitive memory engine with 10 processing phases, multi-pathway retrieval, and causal reasoning built in.
The 10-Phase Pipeline
Every memory operation passes through 10 distinct phases — from input processing to explainability.
Phase 1: Input Processing
Raw input is analyzed, tokenized, and prepared for multi-pathway encoding.
response = client.memory.store( text="The user prefers dark mode", context={"source": "settings"})Core Capabilities
Six pillars that make Engramma fundamentally different from vector search.
Cognitive Memory
Not vector search — real memory with encoding, consolidation, and recall. Your AI remembers like a brain.
Causal Reasoning
Ask 'what if?' and 'why?' with do-calculus. Your agent reasons about cause and effect across memories.
10-Phase Retrieval
Multi-pathway retrieval (exact, energy, attention) with confidence routing. The right memory, every time.
Consolidation
Memories strengthen over time through sleep-like cycles. Weak patterns fade, strong ones persist.
Explainability
Every retrieval comes with a full explanation: why this memory, what contributed, what was considered.
Multi-Tenant
Full organization support with roles, API keys, billing, and team management built in.
Architecture
A high-level view of how data flows through the cognitive memory engine.
┌─────────────┐ ┌──────────────────────┐ ┌─────────────────┐
│ Input │────▶│ Multi-Pathway │────▶│ Confidence │
│ Processing│ │ Encoding │ │ Router │
└─────────────┘ │ ├─ Exact (hash) │ └────────┬────────┘
│ ├─ Energy (Hopfield) │ │
│ └─ Attention (xfmr) │ ▼
└──────────────────────┘ ┌─────────────────┐
│ Pattern │
┌─────────────┐ ┌──────────────────────┐ │ Integration │
│ Explain- │◀────│ Retrieval & │◀────└─────────────────┘
│ ability │ │ Ranking │ │
└─────────────┘ └──────────────────────┘ ▼
┌─────────────────┐
┌──────────────────────┐ │ Causal Linking │
│ Consolidation │◀────│ + Regime Detect │
│ (sleep cycles) │ └─────────────────┘
└──────────────────────┘Ready to give your AI memory?
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