Most AI projects stall on the data, not the model
Tags with no context, compression settings that throw away the signal, gaps during upsets, and no link between a tag and the equipment it measures. Fix those first and predictive maintenance gets cheaper, faster, and more believable to the people who have to act on the alerts.
Two ways to start
Historian-to-AI Readiness Assessment
A review of your historian (AVEVA PI, Honeywell PHD, AspenTech IP.21, Yokogawa Exaquantum, or others): tag quality, compression and scan settings, asset context, data gaps, and secure read-only connectivity. You get a ranked list of AI and predictive maintenance use cases your data can support today.
Predictive Maintenance Pilot
Anomaly detection on one critical asset class, an alert workflow your maintenance team will actually use, and documented value from early catches. Built on tools you already own where possible, so the pilot does not become a platform purchase.
Where predictive maintenance pays first
| Asset | Early warning signs in your data | Why it matters |
|---|---|---|
| Reciprocating & centrifugal compressors | Valve temperatures, rod load, vibration, efficiency drift | A single trip can cost a gas plant or refinery unit a day of throughput |
| Turboexpanders | Bearing temperature, seal gas, speed and efficiency trends | Lost NGL recovery while running on the J-T valve |
| Pumps & motors | Vibration, current, seal and bearing temperatures | High-count assets where early catches add up |
| Heat exchangers & fired heaters | Fouling factors, approach temperatures, tube metal temperatures | Energy loss and unplanned cleaning outages |
| Data center chillers, CDUs & UPS | Approach temperatures, flow, power quality, battery health | Cooling or power events in high-density AI halls |
How it works
Connect read-only
Historian exports or read-only OPC UA. Nothing is installed on your DCS or PLC, and nothing can write to the control system.
Assess & rank
We score data readiness and rank use cases by value and feasibility, under a mutual NDA.
Prove it on one asset class
A focused pilot with clear success criteria, before anyone signs a multi-site platform contract.
Vendor-neutral platform selection
AVEVA PI and AVEVA CONNECT, Seeq, AspenTech Mtell, Honeywell Forge, Emerson Plantweb, Cognite, and others all do parts of this well. We help you choose based on your data, your team, and your budget, or prove the value first with the historian and analytics tools you already license. We do not resell software.
Short-staffed plant? Start with ROI AssetIQ
For brownfield plants with one or two people covering controls and reliability, ROI AssetIQ uses the same read-only connection to track asset age, lifecycle and license status, and nuisance-alarm bad actors, with a weekly "act on these" digest.
Related: APC & Industrial AI Optimization · OPC UA Integration · Data Centers