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Prometheus-AI Capabilities
Prometheus Group’s integrated EAM software leverages AI to help you solve boots-on-the-ground challenges, maximizing productivity across your assets and ERP/CMMS.
Challenges Prometheus-AI Solves for Asset Management
Time inefficiency due to manual processes and system limitations
Reactive cycles that drain resources and reduce asset reliability
Increased downtime and rework from gaps and conflicts that surface too late
Siloed information across ERP, maintenance, and operations systems
Slow decision-making due to fragmented, incomplete, outdated data
Inconsistent processes that vary by individual experience and expertise
Steep learning curves when new staff join the team or rotate into different roles
Increased risk and cost due to gaps in data quality and process standardization
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GWOS-AI
Planning & Scheduling
Trained on more than twenty years of maintenance data, GWOS-AI turns a noisy backlog into an executable schedule. Planners reassign resources in natural language and run AI-powered mass changes, while the system places preventive and corrective work and optimizes by crew or location. Step-by-step guidance enforces a standardized approach and cuts onboarding time for the new and rotating crews common to shift-based operations.
DSO
Decision Support & Optimization
In upstream operations, idle time is the most expensive kind. DSO pulls well delivery— permitting, drilling, completion, facilities, and field operations—into a single optimized schedule, using an AI optimization engine built for upstream complexity to assign rigs, crews, and equipment to activities under real-world constraints. Planners build and compare multiple development-plan scenarios in minutes and run "What if?" analysis against cost, production, and KPIs, so a change or disruption can be absorbed without losing the plan—helping operators hit production targets and maximize return on assets.
STO-AI
Shutdowns, Turnarounds & Outages
A turnaround is the largest controllable event of a facility's year and the one most exposed to overrun. STO-AI accelerates work-package creation with standardized templates, historical norms, and ERP data, while models trained on decades of operational history produce more accurate schedules, surface risks earlier, and optimize plans before execution. During the event, real-time dashboards and automated shift-change logs keep handovers clean and progress, delays, and resource readiness in full view.
ePAS-AI
Electronic Permitting & Safety
The permit to work is the backbone of industrial safety culture. ePAS-AI guides permit creation—prompting for job description, location, and scope, recommending values from similar historical permits, and pushing back on vague or incomplete entries. Its HIRA module auto-populates hazards and controls by work category, from welding and grinding to electrical, then compares against similar permits to surface missing hazards and quality gaps. Natural-language queries replace filter-building—how many hot-work permits are active, average cycle time by type, what is awaiting approval—with instant answers. And by tracking isolations and lockouts across permits, it flags conflicts between jobs sharing equipment and mismatched isolation conditions before work begins.
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MDaaS-AI
Master Data as a Service
None of it works on bad data. MDaaS-AI uses AI to standardize, cleanse, and enrich material masters—assigning noun and modifier, parsing manufacturer and part numbers, and analyzing and building out bills of materials against ERP structures. For operators carrying large MRO inventories across complex asset fleets, that means accurate spares, lower supply-chain cost, and a master record the platform can trust.
RapidAPM
Asset Performance Management
Further along the curve, RapidAPM monitors every sensor on every asset, using AI and neural networks to detect reliability and efficiency issues before they become failures — and unplanned downtime now costs large enterprises an estimated $200 million a year. Crucially, it prioritizes alerts, cutting through the flood of notifications operators field every day, so teams act on the signals that matter rather than drowning in noise. McKinsey research suggests predictive maintenance can reduce downtime by 30–50% and extend equipment life by 20–40%, while built-in Value-at-Risk and ROI calculators put a number on each avoided failure.
Prometheus-AI Advantages
Connected data across your ERP, CMMS, and Prometheus solutions—replacing silos with a single source of truth
More time spent on high-value work as routine, repetitive tasks are automated
Improved safety and compliance through standardized processes, consistent documentation, and clear audit trails
Reduced downtime and rework by surfacing conflicts and gaps before work begins
Shift from reactive to proactive maintenance through predictive insights that get ahead of asset failures
Lower operational costs from decisions backed by historical patterns, best practices, and accurate data
How has Prometheus-AI changed the way you work? We'd love to hear about your experience and the impact it's made on your maintenance operations. Share your Prometheus-AI journey with us and inspire other asset management professionals.
