The Data Is Already There

Pipeline integrity teams have been generating, storing, and managing asset data for decades. Cathodic protection readings from test stations along thousands of miles of alignment. Inline inspection results from scheduled pig runs. SCADA telemetry recording operating conditions continuously. GIS records establishing geometry and right-of-way context. Environmental data showing soil characteristics, climate exposure, and geohazard mapping. Regulatory filings documenting compliance posture over time. And the work history of every action ever taken on every segment, captured in whatever enterprise asset management system the operator has used as the system of record.

The data exists. It is paid for. It is retained as required by regulation and policy. The investment in generating, transmitting, and storing this data over the past two decades has been substantial. And in many operating environments, the value it could produce is sitting unrealized in the enterprise asset management (EAM) system where it has been stored.

The reason is structural. The systems that have housed integrity data for the last two decades were built to record what happened, not to support what should happen next. They preserve the data well. They do not activate it. The integrity team gets a paper trail; what they need is a decision support layer that brings intelligence to the data they already own.

An industry milestone last September brought this question into the open for many operators. IBM's end of base support for Maximo Asset Management 7.6.1.x [1] forced a fresh look at where integrity data should live going forward. This article is for the integrity leaders, asset managers, and operations directors at midstream companies working through that question. It does not advocate one path. It lays out the paths available, names what each one preserves and what each one does not change, and describes the carve-out option in enough detail for the reader to evaluate whether it fits their situation.

What Maximo Has Done Well

Operators have invested in Maximo for good reasons. Generic EAM systems, Maximo included, do real work that the enterprise depends on. They manage spares inventory across multiple sites. They schedule and track enterprise labor. They handle procurement workflows that tie back to the operator's financial systems. They maintain records on rotating equipment with maintenance histories that span years. They support facilities maintenance work that has its own cadence. They produce the financial and operational records that the enterprise needs to run.

For these capabilities, generic EAM is the right tool. Operators who have invested in Maximo are not facing a situation where the platform has failed them on the work it was built for. The platform has done that work, and continues to do it, well enough that operators have built operational habits around it. Procurement teams know the workflow. Maintenance schedulers know the screens. Finance teams know how the data rolls up.

This article is not arguing that any of this should change. The enterprise capabilities that Maximo provides for spares, labor, procurement, and rotating equipment are capabilities the operator should keep. The question this article asks is different. It is whether the pipeline integrity asset class, which has structural requirements that generic EAM was not built for, belongs in the same system as the rest of the asset base.

Where Integrity Work Has Structural Requirements Generic EAM Was Not Built For

Pipeline integrity assets do not fit the generic EAM model cleanly, and integrity teams have been working around this for years. The mismatch is structural, and any integrity manager reading this article will recognize the pattern.

A pipeline segment is not an isolated asset that occasionally requires work. It is a continuously monitored, spatially distributed object whose condition is established by the correlation of multiple data sources. Cathodic protection measurements from test stations along its alignment. Inline inspection results from periodic pig runs. SCADA telemetry from operating conditions. GIS data establishing its geometry and right-of-way context. Environmental data showing soil conditions and geohazard exposure. Regulatory data establishing its compliance status. The work that the integrity team performs is itself driven by what the correlation of these sources indicates.

In a generic EAM, the integrity team can record that work happened. They can attach reports, log labor, and produce a paper trail. What the generic EAM cannot do is tell the integrity team where the next work should happen, why it is the highest priority, and how it relates to the condition history the data has been recording. The integrity team has to do that work themselves, outside the EAM, in spreadsheets, in vendor portals, in whatever ad hoc combination of tools they have assembled. The EAM records the consequence of integrity decisions; it does not support the decisions themselves.

This is the mismatch operators have been feeling. The September 2025 deadline made it impossible to keep deferring.

The Paths Available to Operators

Operators evaluating their EAM options after the September 2025 milestone have several paths available. Each preserves something. Each leaves something unchanged. The article describes them in turn so the reader can see them side by side.

The first path is migration to the IBM Maximo Application Suite (MAS). This is IBM's stated path forward and it is the natural choice for operators whose enterprise EAM investment is well-aligned with their actual operational needs. MAS preserves the work order, spares, labor, procurement, and enterprise reporting capabilities the operator has been using, in a cloud and container-based architecture. The migration carries cost and effort, and the AppPoints licensing model requires careful evaluation, but the path is well-defined and IBM is investing in it as the future of the product line. What MAS does not change is the structural mismatch between generic EAM and pipeline integrity work. The integrity team's experience of working around the EAM does not improve because the EAM moves to a new infrastructure.

The second path is Extended Support through September 2026 or Sustained Support through 2030. This defers the architectural decision. It can be the right path for operators whose plans for replacing their EAM are not yet mature, or who have other priorities competing for the IT organization's capacity. What this path does not solve is the underlying question. By the time Sustained Support ends, the operator faces the same decision they face today. The deferral buys time; it does not resolve the structural mismatch.

The third path is a carve-out of the pipeline integrity asset class to a platform built for that asset class specifically. The enterprise EAM, whether Maximo 7.6.1.x with Extended Support or MAS or a successor product, continues to be the system of record for the asset classes it was designed for. The integrity asset class moves to a platform where the correlated view of integrity data is the central object. The two systems integrate through bidirectional work order flow so the enterprise workflow remains coherent. This is the path the rest of this article describes in detail.

The article does not argue that the carve-out is the right path for every operator. Operators whose integrity work is well served by their current EAM should stay there. Operators planning a comprehensive MAS migration may find that the migration timeline absorbs the integrity question alongside the broader transition. The carve-out is the right path for operators who recognize the structural mismatch, who want the integrity asset class to have the platform it needs, and who want to preserve the rest of their EAM investment without disruption.

What the Carve-Out Actually Looks Like

Before describing what VeriCorr does for the integrity asset class, it is worth naming what VeriCorr does not require. The platform does not ask operators to generate new data. It does not require new sensors, new instruments, or new field protocols. The operator already has the data. What the platform brings is the architectural capability to read that data where it lives, correlate it across sources, and produce intelligence the operator's existing systems cannot.

VeriCorr is built around a different central object than a generic EAM. Where the generic EAM is built around the work order, VeriCorr is built around the correlated asset view. The correlated view is what every other capability in the platform operates on. The architectural choice has four practical consequences worth describing.

The Correlated Data Model

VeriCorr reads from the systems where the operator's integrity data already lives. SCADA historians supply continuous telemetry. Inline inspection vendor systems supply anomaly data. CP databases supply cathodic protection measurements. GIS platforms supply asset geometry, alignment data, and right-of-way context. Environmental data sources supply soil characteristics, climate exposure, geohazard mapping, and watershed proximity. Regulatory data sources supply filing status and audit history. The enterprise EAM, where present, supplies work order history and equipment records.

The platform does not migrate this data out of the operator's source systems. It reads on demand, treats each source as authoritative for its own data, and produces the correlation as a derived view computed continuously rather than stored as a copy. This means the operator never loses control of their underlying data. The platform reads. The platform does not own.

The correlation across these sources is not a feature layered on top of the data model. It is the data model. Linear referencing aligns inline inspection anomaly positions, CP station numbers, SCADA equipment tags, GIS coordinates, and 811 notification points to the same foot of pipe. Temporal alignment makes data captured at different cadences legible at the same moment. Schema reconciliation translates between systems that were never designed to share information directly. The correlated view is what the platform is, not what the platform produces from underlying data that lives separately.

Intelligence at the Core, Not at the Edge

The architectural shift from a generic EAM with AI added to a platform with intelligence at the core is structural. In a generic EAM with AI capabilities layered on, the AI operates at the edge of an architecture that was not built for correlation. It reaches across silos to assemble a partial picture from systems that record their data independently. In VeriCorr, the AI operates on a data model where the correlation has already happened, and the intelligence is a foundational property of the platform rather than a feature added later.

VeriCorr runs dedicated machine learning models on the correlated view. The current model set includes anomaly detection models that identify patterns in the integrity data that warrant review, predictive failure models that surface the likelihood of failure modes based on the operator's specific system characteristics, and growth rate models that project how observed anomalies may evolve over operational time horizons. These are platform-native models built for the integrity domain, not general-purpose machine learning capabilities applied to integrity data.

The architecture is built for continuous learning. As the operator's system generates new data, and as field observations refine the data the platform has already ingested, the models improve. Models trained on an operator's specific system characteristics become more accurate for that operator over time, because they are trained on the operator's data within the operator's tenant.

AI access is tenant-isolated. The persistent chat interface operates on the correlated view through tool-mediated access scoped to the active tenant. Customer data is not exposed to public language models. The AI does not have access to other tenants' data. This is the same data sovereignty principle that governs the rest of the platform, extended to the AI layer.

Bidirectional Work Order Integration with the Enterprise EAM

This is the capability that makes the carve-out viable in practice. Work orders generated from integrity findings in VeriCorr flow bidirectionally with the operator's enterprise EAM, whether that is Maximo, MAS, or another ERP. The integrity team works in VeriCorr because that is where the asset context, the correlated data, the AI-assisted decision support, and the historical risk picture live. The work orders generated from that work are visible in the enterprise EAM, where the operator's labor scheduling, procurement, financial reporting, and enterprise records continue to live.

When a work order is updated in the enterprise EAM, the update flows back into VeriCorr. The integrity team sees the same status the rest of the enterprise sees. The audit trail is complete in both systems. The financial reporting in the enterprise EAM continues to include the integrity team's work. The labor and parts costs continue to roll up correctly. The enterprise's procurement workflow continues to operate as it always has.

The practical effect is that the carve-out preserves what the enterprise EAM does well while moving the integrity work to a platform built for it. The operator's IT organization, finance organization, and procurement organization continue to operate against the enterprise EAM. The integrity team operates against VeriCorr. The work orders link the two.

The Closed Loop Between Field Execution and Model Improvement

Field data captured by the integrity team flows back into the correlation engine immediately. Field observations are geo-referenced and time-stamped at capture. The data joins the correlated view at the moment of capture, becomes available to the engineering team for decision support, and feeds the platform's machine learning models as part of their continuous improvement.

The closed loop matters because it changes what the field execution work produces. In a generic EAM, the field team's work produces a record of what was done. In VeriCorr, the field team's work produces a record of what was done and an improvement in the platform's ability to predict what should be done next. The same field observation that closes a current work order also refines the model that will prioritize the next work order. The improved model prioritizes the next field execution more accurately. The cycle is continuous, and its mechanism is the geo-referenced field data feeding directly into the correlation engine and through it to the models.

Why the Carve-Out Is a Prudent Path

The word prudent is doing real work in this article and it deserves to be earned. The carve-out is prudent for four specific reasons.

First, it is bounded. The carve-out applies to the integrity asset class only. The rest of the enterprise's asset management can stay where it is. The operator is not committing to replacing their EAM. They are committing to giving one asset class a platform built for it. This is a smaller, more reversible decision than a comprehensive EAM transition.

Second, it preserves the operator's existing investments. The enterprise EAM continues to handle spares, labor, procurement, rotating equipment, and facilities work. The MAS migration path is not foreclosed by the carve-out; an operator can carve out the integrity asset class today and migrate the rest of their EAM to MAS on whatever timeline makes sense for them. The two decisions are independent.

Third, it does not require data migration. The operator's integrity data stays in the systems where it already lives. VeriCorr reads from those systems and produces the correlated view as a derived layer. If the operator decides at some point that the carve-out was not the right choice, they have not migrated their data into a platform they would then need to migrate out of. The architectural commitment is bounded; the operator's data sovereignty is preserved.

Fourth, it integrates with the enterprise workflow rather than disrupting it. The bidirectional work order flow means the carve-out does not break the operator's existing tracking, reporting, or financial systems. The enterprise continues to see what the integrity team is doing. The integrity team continues to participate in the enterprise's operational rhythm. The carve-out is an addition to the operator's architecture, not a substitution.

When the Carve-Out Is Not the Right Choice

Honesty about scope is part of what makes a positioning argument credible. There are operators for whom the carve-out is not the prudent path.

For operators whose integrity work is well served by their current EAM, the carve-out does not solve a problem they are experiencing. Some operators have built sophisticated correlation work using their existing tools and have the engineering capacity to maintain it. For these operators, MAS migration or Extended Support may be the right answer; the carve-out adds architectural complexity without resolving a need they do not have.

For operators in the middle of a comprehensive MAS migration, adding the carve-out as a parallel project may exceed organizational bandwidth. The right move may be to complete the MAS migration first and revisit the integrity asset class question after the larger transition settles.

For operators whose integrity team and IT organization do not have the operational alignment to support a carve-out, the architectural choice may be premature. The carve-out works when both organizations understand the bidirectional integration, the data sovereignty model, and the change management implications. If that alignment is not in place, the architectural argument is correct but the operational readiness is not.

The carve-out is the right path for operators who recognize the structural mismatch between generic EAM and integrity work, who want the integrity asset class to have a platform built for it, and who have the organizational alignment to make a bounded architectural change. For operators outside these criteria, other paths are more prudent.

If This Reflects a Question Your Team Is Working Through

If the structural mismatch this article describes is something your team has been working around, and if the carve-out option seems worth evaluating against your specific situation, we welcome the conversation. The first conversation is not a sales conversation. It is a working session that examines your integrity data sources, your enterprise EAM, your team's current workflow, and the question of whether the carve-out architecture would address what you are trying to solve.

Reach us by email at team@vericorr.com, send a note through our connect form, or request a working session on our calendar.

Your data is already there. VeriCorr produces the intelligence your systems cannot.

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Published by VeriCorr. VeriCorr is a pipeline asset integrity intelligence platform headquartered in Fort Worth, Texas. Correlations across inline inspection, cathodic protection, SCADA, environmental, and regulatory data are presented in a single asset view.