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The SEMQ Group

Symbolic Representation Layer for AI Systems

Andrés Mac Allister
Buenos Aires, ARG

SEMQ Group is building a new infrastructure layer for artificial intelligence by transforming embeddings into compact symbolic representations. While embeddings have become a core foundation of modern AI systems, their continuous vector form makes them costly to store, difficult to version and unstable across time and models.

SEMQ addresses these limitations by converting embeddings into symbolic codes that preserve semantic structure while enabling extreme compression, deterministic reproducibility and stable semantic identity. This unlocks a new foundation for scalable AI systems: persistent memory for agents, semantic routing, reproducible AI pipelines and more efficient large-scale architectures.

SEMQ's mission is to help define the next generation of AI infrastructure — systems that are more efficient, interpretable, reliable and built for persistent intelligence.

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