Who we are

David is a passionate advocate of Hyperdimensional Computing (HDC) and its potential to reshape the way we process and understand information. He's constantly thinking about how to model data so that agents can learn, evolve, and collaborate without a human in the loop for every decision.

David's core focus is bridging theory and deployment: taking principles from neuromorphic computing and vector symbolic architectures and turning them into systems that adapt and optimize themselves in production.

Prashanth works at the intersection of data infrastructure, graphs, and agentic systems. He's constantly thinking about how graph and vector representations can be combined so that agents retrieve better context than either is able to provide on its own.

Prashanth regularly builds benchmarks and end-to-end case studies that put the tradeoffs between tools and techniques across HDC, graphs, and vector search on the record, enabling architectural decisions to be based on tangible evidence rather than claims.

Amy is a recognized authority in graph data science, knowledge graphs, and graph for AI. She brings proven expertise in market positioning and go-to-market strategy for emerging tech, built over decades at companies like Neo4j, Cray, and HP.

She is the co-author of the O'Reilly books "Graph Algorithms" and "Knowledge Graphs", and built GraphGeeks from scratch into a vibrant, highly successful practitioner community anchored in trust and relationships.

At HDC Labs, Amy bridges deep cognitive computing with real-world market needs, guiding strategy across positioning, enterprise use cases, and graph-driven applications.