Aveva & IFS launch asset decision intelligence tie-up

AVEVA and IFS have formed a technology partnership centred on a joint offer called Continuous Asset Decision Intelligence.

The arrangement is designed to link operational data, maintenance activity and capital planning for industrial groups managing complex assets. It targets sectors where information on equipment condition, work planning and investment decisions often sits in separate systems.

At the centre of the collaboration is a shared workflow intended to help organisations move from identifying an equipment issue to deciding whether to repair, defer or replace an asset. The model combines real-time operational information with maintenance records, outage plans, spare parts data, crew availability and broader investment priorities.

The focus reflects a long-standing problem in heavy industry. Operations teams may spot an anomaly in live data, but maintenance planners and capital teams often work with only part of the picture. That can make it harder to judge the seriousness of a problem or compare options across a wider asset base.

AVEVA, based in Cambridge, develops industrial software used by manufacturers, energy companies and other process industries. IFS sells business software to asset-intensive industries, including tools for maintenance, service management and capital planning.

Under the partnership, the two groups plan to connect AVEVA's operational and engineering software with IFS systems for enterprise execution and investment planning. Users should then be able to follow a single decision path from an initial asset alert through to the action taken and the eventual result.

Closing gaps

The companies used the example of a utility operating hundreds of substations to show how the system would work. In that scenario, signs of a transformer problem at one site, such as rising temperatures or abnormal dissolved gas readings, would be assessed alongside maintenance history, criticality, available parts, workforce availability, outage planning and the wider capital programme.

That would allow teams to weigh repair, delay or replacement options against previous failures elsewhere in the fleet, while also scheduling the necessary workers and materials. The process would also leave an evidence trail from the first sign of trouble through to remediation.

Caspar Herzberg, Chief Executive of AVEVA, said the partnership addresses a broader industrial need to connect operational data with board-level decision-making.

"Industrial intelligence only becomes real when you have the complete picture. Our partnership with IFS connects data and insights in powerful new ways, from sensor to boardroom. The architecture is right, the customer need is urgent, and the AI opportunity is now practical. This is what radical collaboration looks like in reality," Herzberg said.

Mark Moffat, chief executive of IFS, said the link between asset data and action is central to the project.

"IFS helps customers turn asset insight into action across maintenance, service, workforce and capital planning. Together with AVEVA, we can give customers the operational context and enterprise AI they need to decide what work to do, when to do it, and whether to repair, defer or replace - with evidence from signal to outcome," Moffat said.

Operational pressure

The partners argued that industrial operators face growing pressure to make faster decisions on maintenance and investment while also keeping a clear audit trail. That matters not only for day-to-day reliability, but also for boards, investors and regulators that increasingly want to understand how spending decisions tie back to asset condition and performance outcomes.

They also said the tie-up could reduce the need for custom point-to-point integrations between information technology and operational technology systems. Instead, the approach is described as a platform-to-platform architecture intended to simplify how operational and enterprise software exchange data.

Among the areas highlighted were capital allocation, reliability and compliance. Combining asset health information with investment planning should help teams rank projects by risk, while automated prioritisation of maintenance work could cut the lag between fault detection and response from days or weeks to hours.

External industry analysts also backed the rationale for the partnership. Jeffrey Hojlo, research vice president for industrial ecosystems, manufacturing insights, engineering and product innovation strategies, said the collaboration addressed a weak point in industrial AI adoption.

"AVEVA and IFS are addressing one of industrial AI's biggest gaps: the distance between insight and action. By unifying real-time operational intelligence with enterprise execution and capital planning, their partnership promises to deliver Continuous Asset Decision Intelligence across the asset lifecycle. The closed-loop enterprise-to-production-to-edge digital thread that this partnership enables also provides a foundation upon which generative, agentic and predictive AI can advance data analysis and federation, enhance knowledge sharing, and improve both planning and risk management," Hojlo said.

Craig Resnick, vice president at ARC Advisory Group, said the approach could help industrial groups make more consistent and traceable decisions.

"What makes this AVEVA-IFS partnership compelling is that it closes the distance between insight and action. By connecting real-time operational intelligence with enterprise execution and strategic capital planning, 'Continuous Asset Decision Intelligence' turns often thousands of data points into a single, evidence-based decision flow - so teams can decide what work to do, when to do it, and whether to repair, defer or replace with greater speed and confidence. Just as importantly, it creates an auditable chain from asset condition to decision to outcome, which is increasingly critical for boards, investors and regulators."