Industrial Intelligence
AI grounded in engineering context.
Industrial environments bring together physical processes, technical knowledge and decisions with real consequences. We are exploring how specialized models can work with engineering tools and operational information to support investigation and decision-making.
Our direction starts with resource-intensive operations, including water, and extends toward other industrial domains. We aim to develop specialized models on OMN and supporting systems that help people interpret technical information, investigate problems and assess possible actions.
We are exploring on-premises deployment and learning from permissioned, domain-specific evidence. Local deployment can offer greater control over data flows; it does not by itself guarantee security. Any use of operational data for model improvement would require appropriate rights, evaluation and controlled versioned updates—not unchecked learning from every interaction.
This is a research direction, not a claim of deployed industrial capability. Our aim is decision support with traceable evidence and human oversight. Plant control, safety interlocks and authorization remain separate responsibilities.
Domain specialization
Investigating OMN-based models trained and evaluated for technical language, domain concepts and industrial workflows. Specialization must be demonstrated on representative tasks, not inferred from a domain label.
Engineering-grounded systems
Exploring how specialized models can work with authorized operational records, calculations and engineering tools. Model-generated explanations remain distinct from measured data, validated calculations and control-system decisions.
Evaluation in context
Assessing usefulness, reliability and limitations on representative tasks, establishing empirical benchmarks that measure decision quality in high-consequence operational settings.
We will share specific projects and findings as they are ready for public release. Follow our Updates log for ongoing research and technical notes.