We help process plants understand problems, use existing systems where they work, and add only what is missing. Not every engagement involves AI.
Find the problem worth solving.
Plant problem identification, readiness assessments, working sessions, workshops, value and feasibility review, pilot selection, and a 30/60/90-day roadmap where appropriate.
Not every problem requires AI. The response may be a work-process change, better instrumentation, control improvement, reliability work, conventional analytics, or first-principles engineering. We will say so when AI is not useful.
See also Workshops and Assessments below.
Industrial Data & Context Integration
Bring together the information needed to understand the problem. Useful data often already exists across DCS, PLC, SCADA, historian, CMMS/EAM, ERP, LIMS, alarms, engineering documents, SOPs, P&IDs, maintenance history, equipment information, and operator observations.
The objective is usually not to replace these systems. It is to connect the relevant information and add enough context — equipment, asset hierarchy, time, operating state, process relationships, maintenance history, engineering knowledge — to make it useful for engineers, operators and maintenance staff.
Use what already works. Build only what is missing.
Buy what fits. Build what is missing. Own what matters.
Use proven commercial products for common requirements where they make economic and technical sense.
Do not replace functioning plant systems unnecessarily. Connect historians, maintenance systems, control systems and documents that already run the plant.
Commercial software is often the right answer. When plant-specific gaps would mean heavy customization, licensing, support and supplier dependence, a focused application can be the simpler path. That does not mean asking a language model to write an industrial application unchanged.
Open-source tools and AI-assisted development have lowered the effort and cost threshold at which focused custom applications become worth considering.
Retain reasonable control of plant data, workflows, engineering knowledge, and the ability to maintain or evolve the application. The goal is to reduce unnecessary supplier dependency, not to promise complete independence from suppliers.
We consider total lifecycle cost, not purchase price alone. Relevant costs may include licenses, configuration, integration, custom development, consulting, upgrades, support, training, maintenance, internal capability, and supplier dependence.
Put the solution into the actual work.
Technology creates value when it is used in operations, maintenance, reliability, process engineering, automation/process control, IT/OT, and by supervisors and management.
We support workflow integration, training, change management, governance, ownership, human review, performance measurement, and continuous improvement.
AI suggests. Your staff decide. We do not imply autonomous operation of process plants.
Focused working sessions for cross-functional plant teams. Scope and commitments are on the workshop pages.
Optional anonymous surveys to explore themes before a deeper engagement. There is no obligation to submit. Responses are aggregated; they are not shared publicly.
AI readiness workshop survey — ~8–12 minutes Preliminary plant reliability assessment — ~10–15 minutes Preliminary plant automation maturity assessment — 25 questions, ~10 minutes
For teams ready for a more detailed automation maturity picture:
Full plant automation maturity assessment — 127+ questions, ~45–60 minutes