Solutions
Engineering Intelligence Applied to Real Operational Challenges
McC AI Group develops deployable solutions that apply Engineering Intelligence to specific operational challenges in regulated and mission-critical facilities.
Each solution integrates advanced AI and engineering algorithms with verified operational information, site-specific engineering knowledge, explainable reasoning, and governed control. Rather than replacing existing automation infrastructure, our solutions are designed to operate as supervisory intelligence layers that work with established plant data, instrumentation, PLC/SCADA systems, equipment, and operating procedures.
Our solutions are built from four coordinated core modules—OperationsAI, SensorAI, WisdomAI, and PilotAI—configured according to the technical requirements, operational objectives, information reliability, engineering constraints, and authority appropriate for each application.
AerationAI™
Real-Time Dynamic Aeration Optimization
AerationAI is a standalone Engineering Intelligence solution for real-time wastewater aeration optimization.
AerationAI uses plant-specific predictive algorithms to determine aeration requirements as wastewater flow, loading, temperature, biological activity, equipment conditions, and treatment demands change. Rather than relying solely on fixed dissolved-oxygen setpoints, the system computes plant- and basin-specific base airflow requirements and continuously evaluates appropriate airflow adjustments.
The objective is not simply to reduce airflow. AerationAI seeks the most energy-efficient aeration condition consistent with treatment performance, process stability, equipment capability, effluent requirements, and approved operating authority.
AerationAI integrates process monitoring, sensor-reliability assessment, predictive aeration modeling, anomaly detection, engineering constraints, operating-envelope governance, supervisory recommendations, and bounded control.
When suitable instrumentation, operational data, and control interfaces are already available, AerationAI can normally operate through existing sensors, PLC/SCADA systems, blowers, VFDs, valves, dampers, and aeration infrastructure without requiring new process hardware or major physical plant modifications.
Key capabilities include: real-time base-airflow computation; continuous airflow adjustment; energy and treatment co-optimization; sensor-reliability evaluation; basin and equipment coordination; plant-specific operating envelopes; bounded supervisory control; operator oversight, override, and configured fallback to existing control.
AerationAI-SND™
Governed Low-DO Simultaneous Nitrification and Denitrification
AerationAI-SND extends the AerationAI architecture to controlled low-dissolved-oxygen operation for simultaneous nitrification and denitrification.
Operating biological treatment at sustained low DO can create significant opportunities for aeration-energy reduction and nitrogen removal, but the operating margin between excessive aeration and insufficient oxygen can become narrow. Biological response, sensor reliability, hydraulic transport, oxygen-transfer performance, temperature, loading, and nitrifier condition must therefore be considered together.
AerationAI-SND combines plant-specific predictive aeration with sensor-confidence evaluation, oxygen-availability assessment, biological-risk indicators, time-based operating envelopes, multi-zone airflow distribution, and bounded supervisory authority.
The objective is not to drive DO to the lowest possible concentration. The objective is to establish and maintain the lowest appropriate and governable oxygen condition that supports nitrification, creates opportunity for denitrification, reduces unnecessary aeration, and protects biological stability and effluent performance.
AerationAI-SND can begin in shadow or advisory operation and progressively advance toward governed low-DO supervisory control as information reliability, model performance, biological stability, operator confidence, and facility authorization are established.
Key capabilities include: predictive low-DO aeration control; simultaneous nitrification-denitrification support; oxygen-supply and biological-demand evaluation; multi-zone operating envelopes; sensor-confidence assessment; biological-risk governance; nutrient-removal performance monitoring; bounded trim control; staged supervisory authority; operator intervention and fallback.
Sensor Reliability Governance™
Trusted Measurements Before Trusted Decisions
Reliable automation depends on reliable information. A process measurement can continue producing numerically plausible values even when fouling, drift, bias, calibration loss, communication problems, or abnormal operating conditions make that measurement unsuitable for supervisory decisions.
Sensor Reliability Governance evaluates whether operational measurements remain trustworthy enough to support monitoring, optimization, recommendations, or control.
The architecture combines operational-consistency assessment, cross-sensor and peer comparison, process relationships, virtual sensing, confidence-weighted estimation, and supervisory restrictions when measurement confidence declines.
Rather than treating sensor validation as a separate maintenance function, sensor reliability becomes part of the decision-governance architecture itself. The level of operational authority can therefore reflect not only the proposed action, but also the confidence in the information supporting that action.
Key capabilities include: operational-consistency assessment; drift, bias, and failure detection; cross-sensor and peer comparison; virtual-sensor validation; confidence-weighted estimation; sensor-reliability scoring; supervisory bounds based on information confidence; and auditable reliability and decision records.
Explore Sensor Reliability Governance →
Custom Engineering Intelligence Solutions
Extending Engineering Intelligence Beyond Current Applications
The Engineering Intelligence architecture is not limited to wastewater aeration.
McC AI Group can configure solution architectures for other regulated industrial and critical-infrastructure applications in which operational decisions must be supported by reliable information, engineering knowledge, transparent reasoning, and enforceable governance.
Development begins with the decision that must be trusted.
From that decision, the required operational information, engineering relationships, predictive or optimization algorithms, process constraints, operating envelopes, authority limits, integration requirements, validation criteria, and deployment pathway are defined.
Custom solutions can incorporate existing facility instrumentation and automation systems while adding the supervisory intelligence required to improve decision quality, operating performance, reliability, energy efficiency, resilience, or regulatory assurance.
Applications may begin with analysis or advisory recommendations and advance toward bounded supervisory control only where technical validation, operational confidence, engineering review, cybersecurity requirements, and facility authorization support expanded authority. This staged approach is consistent with the deployment architecture already used in AerationAI and AerationAI-SND.
Powered by Four Core Engineering Intelligence Modules
Every McC AI Group solution draws upon four coordinated modules that provide the underlying Engineering Intelligence architecture.
OperationsAI™ — Operational Objectives and Optimization
Defines operational objectives, models facility-specific processes, establishes optimization strategies, identifies engineering constraints and information requirements, and develops the decision and control logic required for the application.
SensorAI™ — Trusted Operational Information
Evaluates measurement integrity, validates operational information, supports virtual sensing, identifies unreliable signals, and establishes confidence in the information used for recommendations and control.
WisdomAI™ — Engineering Knowledge and Explainable Reasoning
Applies site-specific engineering knowledge, operating experience, domain models, engineering principles, standards, constraints, and context-aware reasoning to interpret conditions and evaluate appropriate responses.
PilotAI™ — Governed Decisions and Actions
Evaluates proposed recommendations and actions against information confidence, operating envelopes, engineering constraints, equipment limits, organizational authority, and fallback requirements before allowing operational authority to advance.
Together, these modules enable Engineering Intelligence to progress systematically from:
Operational objectives → Trusted information → Engineering knowledge and reasoning → Governed decisions and actions
The modules are reusable architectural capabilities. AerationAI, AerationAI-SND, Sensor Reliability Governance, and future application-specific systems are the deployable solutions built from those capabilities.
Governed Deployment
Engineering Intelligence is designed to earn operational authority progressively rather than assume it from the outset.
A solution may begin by analyzing historical and real-time information, proceed through shadow-mode verification and advisory operation, and advance to limited or expanded supervisory authority only when performance, information reliability, engineering safeguards, cybersecurity requirements, operator readiness, and facility authorization justify progression.
Existing operational controls remain part of the architecture. Operators retain appropriate visibility, intervention authority, override capability, and configured fallback throughout deployment.
Operational authority expands only as evidence, confidence, engineering validation, and site authorization justify it.
Engineering Intelligence for Your Facility
Every facility has different objectives, process configurations, instrumentation, operating histories, control systems, regulatory requirements, and organizational constraints.
McC AI Group begins with the operational problem and the decisions that matter—not with a predetermined technology package.
We evaluate how advanced AI, engineering algorithms, existing operational information, site-specific engineering knowledge, and governed control can be integrated to create a practical Engineering Intelligence solution for the facility.We evaluate how advanced AI, engineering algorithms, existing operational information, site-specific engineering knowledge, and governed control can be integrated to create a practical Engineering Intelligence solution for the facility.
McC AI Group, Inc. 