Engramma
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Insights & deep dives

Technical deep dives on AI memory, cognitive architecture, and building intelligent agents.

ArchitectureComparisonTutorial
Comparison4 min

Engramma vs Pinecone vs Weaviate: A Technical Comparison

An honest side-by-side comparison of Engramma, Pinecone, and Weaviate — architecture, retrieval models, pricing, and when to use each.

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Abdel Hakim
Tutorial4 min

How to Add Persistent Memory to Your AI Agent (2026)

Step-by-step guide to giving your AI agent long-term memory with Engramma — from zero to a working agent that remembers across sessions.

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Abdel Hakim
Architecture5 min

Why Vector Databases Are Not Memory

Vector databases retrieve similar content. Memory requires reasoning, temporal awareness, and consolidation. Here is why the distinction matters for AI agents.

A
Abdel Hakim
Architecture6 min

The 10-Phase Cognitive Retrieval Cycle Explained

A deep technical dive into Engramma's 10-phase cognitive retrieval cycle — how queries flow through encoding, pathway selection, temporal weighting, causal traversal, and confidence scoring.

A
Abdel Hakim