The Geometry of
Intelligence.
The ecosystem is fracturing into specialized domain models. We are architecting the geometric protocols to align these disjointed latent spaces and bridge isolated intelligence.
The Case for Latent Interoperability.
In this briefing, founder Jonathan Politzki explains the case for interoperability between embedding systems, and how geometric representations provide the solution.
Commissioned Research
We partner with select organizations to solve hard technical problems in memory systems, latent space navigation, and model alignment.
Publications
2026 ARCHIVEThe State of AI Memory 2026
A comprehensive review of the current landscape, from RAG to long-context windows and beyond. Analyzing the technical tradeoffs between context injection, fine-tuning, and memory-augmented generation.
Latent Space Alignment via Manifold Projection
Politzki, J. et al. — Exploring zero-shot transfer capabilities across disjoint embedding spaces.
The Fragmented World
The Tower of Babel is being rebuilt. As Silicon Valley floods the market with specialized models, we are witnessing a divergence. Knowledge is becoming trapped within incompatible embedding spaces, creating silos of intelligence that cannot speak to one another.
Our research focuses on the Platonic Hypothesis: that different embedding spaces trained on human text tend to share recoverable latent structure. By aligning these manifolds, we can enable seamless communication across the boundaries of different AI systems.
Theory to Infrastructure
We position ourselves at the vanguard—where theoretical breakthroughs in manifold alignment meet the rigorous demands of production systems.
By maintaining deep ties to academic SOTA in representation learning while operating at the cutting edge of industry engineering, we bridge isolated expertise to market. Our infrastructure is built on first principles for practical business applications.