Different systems, same shape.

Metadata governance for the open enterprise data stack.

Automatically classifies database columns against a BFO-grounded ontology using uncertainty-aware Dempster–Shafer evidence fusion. Integrates Impala, Kudu, Iceberg, Atlas, and Ranger into an HMS-free query stack with automated classification and policy enforcement.

Hierarchical sequence modeling with dynamic chunking.

A hierarchical sequence model for semantic column annotation and cross-table data-element discovery on relational data.

A terminal interface for navigating graph-oriented data domains.

Projects high-dimensional embeddings onto a 19×19 grid. Combines a Go-board metaphor with topological data analysis to surface structural patterns in knowledge bases and document collections.

Agentic classification workbench for column-level data governance.

Interactive workbench that fuses six evidence sources — embedding similarity, gradient boosting, regex detection, name matching, short-text SVM, and an LLM convergence agent — through Dempster–Shafer belief functions to produce uncertainty-quantified column classifications.

Reproducible ontology-grounded corpora for data-governance models.

Independently-versioned home for the Signals Data Governance corpora. Each commit is a reproducible convergence snapshot of the whole derivation chain — ontology, SKOS vocabulary, relational footprint, and generated corpus.

Event-sourced actor system for distributed manufacturing.

Process-separated architecture using Apache Kudu for event persistence and Aeron IPC for sub-microsecond inter-process messaging.

A global resource-oriented compute fabric for sovereign and high-latency environments.

Resource-oriented compute fabric in the 1060 NetKernel tradition. Every artifact — raw events, queries, materialized views — is a URI-addressed, content-addressed resource that a kernel resolves to a DataFusion compute endpoint at rest.