Cenosco's AI Plan for Asset Integrity Management (Part 2): Not all RBI tools are made the same

Cenosco builds the Integrity, Reliability, and Functional Safety software that asset-intensive industries use to run their inspection and maintenance programs. RBI sits at the center of the Integrity side of that. In my last article, ‘Cenosco’s AI Plan for Asset Integrity Management,’ I focused on the discipline where Cenosco’ story started – Mechanical Integrity. I wrote about a fundamental paradigm shift required in Asset Integrity: moving from static RBI programs to modern RBI tools that support a more contextual, continuous RBI (living-RBI). I called this dynamic RBI.

Dynamic RBI updates equipment risk and optimizes inspection intervals as operating conditions change and new inspection data become available, ensuring frequencies remain aligned with the asset’s current risk profile.

RBI tools are the software solutions asset-intensive organizations use to assess, prioritize, and manage inspection activities based on risk, rather than fixed time intervals. Advanced RBI tools go beyond static models by incorporating live operational signals, degradation mechanisms, and contextual integrity data.

I focused on RBI first because it’s a business case. RBI is how Asset Integrity teams have justified and secured digitalization budgets for years: the case for moving from time-based to risk-based inspection remains the driver behind most Asset Integrity and Risk Management digital transformation projects.

Cenosco’s vision for next-generation RBI tools carries the potential to meaningfully extend the OPEX savings from static RBI. More importantly, this shift will finally allow asset integrity teams to directly correlate their work to asset uptime, a critical tie-in to revenue protection and relevance.

Here’s the catch: you cannot sprinkle AI on top of a simplified RBI database or a legacy spreadsheet and call it dynamic RBI. Not all RBI tools are made equal. To build advanced RBI tools capable of dynamic RBI, you need the basics of an enterprise-grade asset integrity platform first.

Over the last 25 years, Cenosco has been steadily and systematically building toward this comprehensive vision. With these critical foundational layers now mature, AI is what makes the next leap possible.

Before our AI engine (living-RBI) can calculate an equipment dynamic risk profile, it depends on four interconnected, foundational pillars within IMS’ Mechanical Integrity Software.

Live data is meaningless without context. Real-time RBI must be anchored in physical truth. Through IMS IDMS, the system accesses complete historical inspection reports, corrosion loops, and detailed wall-thickness data. This gives us the exact, verifiable baseline condition of the equipment.

To understand dynamic risk, we need to know what is happening inside the asset right now. IMS IOW continuously tracks live operational parameters, like temperature, pressure, and chemical injection rates and process sampling results. If variables breach the desired limit, the system flags a potential acceleration in degradation rate.

IDMS gives us the history, and IOW gives us the real-time pulse, but neither means anything without something to measure it against. The organization’s approved and governed RBI baseline remains the formal reference point, aligned with applicable regulatory requirements and internal engineering standards. It defines the formal, compliant boundary lines of our inspection strategy, ensuring we always remain anchored in engineering standards such as API 580 and 581.

An asset does not operate in a vacuum. Through our robust CMMS integrations, the system automatically pulls live maintenance records, outstanding work orders, and repair histories from systems like SAP. If a scheduled repair is delayed or a temporary repair is installed, this operational backlog is instantly fed into our risk calculations.

These four pillars, IDMS, IOW, the approved RBI baseline, and CMMS integrations, form the foundation of every modern RBI tool. Without them, no AI engine can be trusted with a live risk calculation.

Here’s where we actually are. That foundation is live in IMS today.

The first real piece of AI on top of it is Degradation Mechanism Recommendations: AI that reviews equipment design and operating conditions, inspection results and integrity status and suggests likely degradation mechanisms for a corrosion engineer to confirm or reject. This isn’t a future promise. It’s the part of dynamic RBI we’re actively building right now.

From there, the path is clear. Once an engine can reliably identify degradation mechanisms, the same approach extends to continuously reassessing risk and, eventually, to the full dynamic RBI engine described below, now in closed beta with open beta planned for Q1-27.

With these four pillars in place, the engine can do its job. The engine combines validated degradation models, historical integrity data, and operational signals. Together, these continuously reassess risk indicators and surface changes that need engineering review.

Once fully in place, these RBI tools will augment the traditional static RBI workflow with a live view of equipment risk and evolving inspection intervals. Instead of waiting for a scheduled five-year review, the risk matrix will update as new evidence appears. This way, the actual risk on the asset is aligned with the dynamically modeled risk.

In highly regulated industries, an RBI program cannot operate on autopilot. Compliance requires formal approval, anchored in established, governed baseline intervals.

IMS balances regulatory compliance with real-time operational reality through a dual-perspective approach. The organization’s approved, governed RBI baseline sits directly alongside a second, live RBI recommendation.

Cenosco built this to ensure that a qualified engineer, the one in the middle, always has the final say. Putting these two data points side by side gives integrity professionals the exact context they need to make high-confidence, individual decisions. It also helps them safely prepare the engineering case needed to extend an interval.

Since releasing the first article, Cenosco has held 60+ in-person meetings with owner-operators globally. Those conversations revealed a shared pain point and an unsurprising UI/UX insight. Integrity teams are highly skilled but chronically stretched. They are bogged down by manual data compilation and reactive workflows. AI is what makes dynamic RBI possible, but the feedback from the field is clear: dynamic RBI will fail at launch if it adds more admin burden on already stretched teams. Users want it to deliver actionable insight faster, at the right place, at the right time.

If live risk updates end up buried inside complex software sub-menus, they won’t drive real-world action.That is why Cenosco is building this engine to be proactive from the ground up, pushing automated daily, weekly, or monthly digest updates straight to the user’s inbox. The engine operates on two levers.

The engine flags assets where live process parameters have stayed exceptionally steady and wall-thickness trends show negligible degradation. It then presents a clear summary of the potential optimization alongside the tangible cost-saving impact of extending that specific inspection window.

Conversely, the engine pinpoints high-risk areas where process limits have been breached or maintenance has been delayed. Even where acting early increases short-term inspection costs, the aim is to make the greater cost avoided clear: preventing a catastrophic, multimillion-dollar unplanned downtime event.

By presenting the live recommendation side by side with the approved, governed interval, and backing it with clear financial metrics, the goal is to bridge the gap between engineering reality and commercial impact, so integrity managers get a data-driven business case, not just a risk score.

From a leadership perspective, the goal of our dynamic RBI technology is to optimize human capital and drive operational efficiency.

We want to move integrity engineers out of spreadsheets and into strategic decision-making, so they no longer hunt for data. Instead, the system is designed to deliver high-confidence, prioritized actions straight to them, freeing teams to proactively mitigate risks before they escalate.

At Cenosco, Goal Zero isn’t an abstraction we put on a slide. It’s the outcome of engineering decisions made early enough to matter. Integrity is maintained by identifying degradation before it leads to a loss of primary containment, validating barriers before they fail, and ensuring known threats never become incidents. Risk-based deferrals are actively governed, ensuring they remain justified and visible.

We believe that achieving that demands an operating model built on continuous intelligence. Next-generation RBI tools that enable dynamic RBI are one of many vehicles that will get us there: driving down inspection costs, reducing unplanned downtime, and helping asset-heavy industries operate at their full, safe potential.

We’re building this piece by piece. Degradation Mechanism Recommendations is the first AI capability we’re actively rolling out on top of the mature IDMS, IOW, RBI baseline, and CMMS foundation already live in IMS today.

Agree with this direction, or see it differently? Talk to me and our integrity engineering team directly at machine.vision@cenosco.com, or message us on our LinkedIn page.