Hypericum

Building the knowledge layer
for enterprise and investment intelligence.

We construct formal taxonomic structures that encode domain knowledge as governed, versioned assets, enabling both AI agents and human teams to discover relevance, automate reliably, and reduce uncertainty.

What we own

Our work sits at the intersection of meaning extraction, dimensional analysis, and structural inference: areas where conventional AI tools reach their limits.

Constructed and curated taxonomies

We build formal taxonomic structures that encode domain knowledge as governed, versioned assets. These are not auto-generated tag clouds. They are precision instruments for classification, retrieval, and analytics.

Associative structure discovery

Drawing on decades of foundational research in natural language processing, our engines detect non-obvious relationships and co-occurrence patterns across high-dimensional data spanning financial, market, government, risk, and enterprise domains. We find what correlation matrices miss.

Deep analytics

Our analytical layer produces defensible, auditable outputs rather than black-box scores. The result is structured insight that decision-makers can act on with confidence.

Our team

Technical work led by Professor Scott Deerwester, a founding pioneer of natural language processing whose research in the 1990s established the mathematical foundations of meaning extraction now used across the field.

Our scientists have advanced the boundaries of human knowledge in natural language processing, artificial intelligence, geometry, and industrial mathematics. Our domain specialists bring deep expertise in alternative asset management, corporate strategy, and data science.

We carefully select our clients and partners. This has allowed us to build a reputable client base globally and maintain the research depth that defines our work.

Building the knowledge layer for enterprise and investment intelligence.

Building the knowledge layer
for enterprise and investment intelligence.