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AI Memory & Cognition Landscape: Deep Dive

In Part 1 of this series, we explored the "Human Blueprint" for AI memory in the context of organizations, the idea that for agents to truly reason, they must mimic the way the human brain balances knowledge, learning, and experience. In Part 2a, we introduced the KMC (Knowledge-Memory-Context) Blueprint to help define the three distinct layers required for an AI to “find”, “learn”, and "understand" so it could “think” like a colleague. Now, we move from theory to the technical landscape.

Blogs

April 30, 2026

Blogs

April 16, 2026

The Spectrum of Machine Cognition: Evaluating Frameworks from Coding Agents to the Enterprise Memory

In this blog, we outline what AI cognition means, establish standard metrics, and introduce the frameworks / tools we have have included in our study. This forms the baseline to understand what’s out there as it’s a rapidly growing market to address a need for Agentic cognition and reasoning.

The Spectrum of Machine Cognition: Evaluating Frameworks from Coding Agents to the Enterprise Memory

Blogs

October 23, 2025

Human Memory As The Perfect Template For AI Memory

This blog explores how human memory inspires the next generation of AI systems that don’t just recall data but learn, adapt, and reason through context. By mirroring how we process multimodal information, AI memory can evolve into a living, dynamic engine for intelligent decision-making.

Human Memory As The Perfect Template For AI Memory

Blogs

February 24, 2026

Context Graphs And Their Implementation: The Missing Layer Between Human Judgment and Machine Agency

Context Graphs are proposed as the system of record for reasoning, capturing and justifying decisions made by both humans and AI agents with high fidelity. This shift requires a technical substrate for scale and a cultural shift towards "reason hygiene" and annotated decision traces. ApertureDB can be the foundation, but a cultural change supported by agent reasoning layer is key to building intelligent, auditable organizations.

Context Graphs And Their Implementation: The Missing Layer Between Human Judgment and Machine Agency

Building Real World RAG-based Applications with ApertureDB

Blogs

November 21, 2024

Building Real World RAG-based Applications with ApertureDB

LLMs, RAGs, Chatbots, Agents. All hot topics! 🔥 But what does it mean to implement these and make them work well? See some real examples built on ApertureDB's purpose-built multimodal vector db.