Research & Insights
Exploring the science behind organizational memory and the future of human-AI collaboration
The Insight Gap
“We're drowning in information, but starved for knowledge”
— John Naisbitt, 1982
This insight, articulated over four decades ago, has never been more relevant. Today's organizations generate unprecedented amounts of data, yet struggle to transform it into actionable knowledge that evolves with their organization.
Our Research Focus
Memory Science
Understanding how organizations create, store, and retrieve knowledge across time and context
AI Collaboration
Exploring optimal patterns for human-AI collaboration in knowledge-intensive work
Impact Measurement
Quantifying the business impact of memory infrastructure on productivity and decision quality
Latest Research
Peer-reviewed studies and original research on organizational memory and AI collaboration
Contextual Memory Intelligence: A Foundational Paradigm for Human-AI Collaboration and Reflective Generative AI Systems
Authors: ReMemora Research Team
This paper introduces Contextual Memory Intelligence (CMI) as a foundational paradigm for human-AI collaboration and reflective generative AI systems. Drawing from cognitive science, organizational theory, human-computer interaction, and AI governance, we propose a comprehensive framework that addresses substantial memory limitations in current AI systems.
Key Findings
- Current generative AI systems have substantial memory limitations that affect decision-making quality
- AI workflows rarely store or reflect on the full context in which decisions are made
- CMI repositions memory as an adaptive infrastructure necessary for longitudinal coherence and explainability
- The Insight Layer architecture enables systems to reason with data, history, judgment, and changing context
Whitepapers & Guides
Coming Soon
Practical guides and implementation frameworks for building organizational memory infrastructure
Collaborate with Our Research Team
Interested in partnering on research or accessing our datasets? We welcome collaboration with academic institutions and research organizations.