Applied research, development, and advisory in hyperdimensional computing.

We work at the intersection of hyperdimensional computing (HDC), graph intelligence, and agentic systems. We design hypervector representations for real tasks, benchmark them against established approaches, and publish what we learn.

Our current interests include:

• connected and heterogeneous data
• associative search and agent memory
• online learning from small numbers of examples
• practical combinations of HDC, graphs, and deep learning

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