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— 03 / Industries

Built for asset-intensive industries.

From aluminum manufacturing and power generation to mining, transportation, oil & gas, and public infrastructure — we modernize asset performance with practical intelligence.

/I.01

Manufacturing

Automotive, aluminum, steel, chemicals, food, consumer goods, aerospace.

/I.02

Energy & Utilities

Power generation, renewables, transmission, pipelines, LNG, refining.

/I.03

Mining & Metals

Surface mining, underground, smelters, concentrators, mobile fleets.

/I.04

Oil & Gas

Upstream, midstream, downstream, offshore, terminals.

/I.05

Public Infrastructure

Ports, waterways, transportation, municipalities, water systems.

/I.06

Life Sciences

Regulated assets, calibration, utilities, production reliability.

/I.01 — Manufacturing

Reliability and throughput across discrete and process plants.

Automotive, aluminum, steel, chemicals, food, consumer goods, aerospace. Decades-old assets, mixed OT vendors, and skilled-labour gaps meeting daily takt-time pressure.

What we hear
  • Unplanned downtime on bottleneck lines is the single biggest profit leak.
  • PM compliance looks healthy on paper, yet failures still surprise the floor.
  • OEE dashboards exist; the actions that move OEE do not.
Where we focus
  • Failure-mode-driven predictive models on stamping, motors, gearboxes, conveyors.
  • EAM redesign in SAP PM or Maximo so the work order reflects the actual asset.
  • Throughput AI on the constraint — scheduling, yield, and changeover loss.
Signature outcomes
  • ↓ 28% unplanned downtime on a single stamping line, year one.
  • ↑ 4.1pt OEE on an aluminum hot-mill bottleneck.
  • ↓ 19% PM hours redirected to predictive without losing compliance.
/I.02 — Energy & Utilities

Generation, transmission, and pipelines under reliability scrutiny.

Power generation, renewables, transmission, pipelines, LNG, refining. Regulators, ratepayers, and ESG investors all watching the same asset base.

What we hear
  • Outage planning is reactive; the system absorbs cost no one budgets for.
  • Historian data is rich, but never reaches the work-management decision.
  • Capital plans are built on age, not on actual condition or risk.
Where we focus
  • Condition-based maintenance on turbines, transformers, and rotating equipment.
  • Risk-weighted capital sequencing tied to regulator and ESG commitments.
  • Outage optimization with constraint-aware scheduling AI.
Signature outcomes
  • ↓ 22% forced outage rate across a 14-asset rotating fleet.
  • ↑ $38M capital re-prioritized away from age-based replacement.
  • ↓ 31% reactive work orders over two PM cycles.
/I.03 — Mining & Metals

Mobile fleets, fixed plants, and brutal duty cycles.

Surface mining, underground, smelters, concentrators, mobile fleets. Remote operations where every hour of downtime is paid for in lost tonnes.

What we hear
  • Haul-truck availability swings 8–12% week to week with no clear cause.
  • Concentrator throughput drifts; root-cause investigations take weeks.
  • Mobile and fixed asset data live in different systems and never converge.
Where we focus
  • Component-level prognostics on engines, frames, and drivetrains.
  • Yield and recovery analytics tied to ore characteristics and operator inputs.
  • One unified asset register across fleet, fixed plant, and infrastructure.
Signature outcomes
  • ↑ 6.8% haul-truck availability on a 110-unit fleet.
  • ↑ 2.3% recovery uplift at a copper concentrator within 6 months.
  • ↓ 41% mean time to detect drivetrain failure precursors.
/I.04 — Oil & Gas

Upstream to downstream, with safety as the only constant.

Upstream, midstream, downstream, offshore, terminals. Integrity, emissions, and turnaround economics all measured to the dollar and to the day.

What we hear
  • Integrity programs are exhaustive but inspection windows still miss real defects.
  • Turnaround scope explodes once work starts and budget never holds.
  • Emissions reporting is manual; signal lags reality by a quarter or more.
Where we focus
  • Risk-based inspection prioritization fed by historian, lab, and field data.
  • Turnaround scope optimization with predictive backlog growth modelling.
  • Methane and emissions analytics aligned to MRV and regulator reporting.
Signature outcomes
  • ↓ 17% turnaround scope creep on a refinery shutdown.
  • ↑ 2.4× defect discovery rate per inspection hour.
  • ↓ 12% reportable emissions through continuous detection.
/I.05 — Public Infrastructure

Ports, transit, and water systems that cannot stop.

Ports, waterways, transportation, municipalities, water systems. Public scrutiny, regulated capital, and asset bases that outlive every administration.

What we hear
  • Asset registers are out of date the moment they're published.
  • Capital plans defend last year's numbers, not next decade's risk.
  • Procurement and maintenance speak different languages about the same assets.
Where we focus
  • Condition-based renewal planning tied to service-level commitments.
  • Geospatial asset intelligence joining GIS, EAM, and SCADA.
  • Defensible long-range capital models for council and board review.
Signature outcomes
  • ↑ 96% asset register accuracy on a 22,000-asset network.
  • ↓ 18% emergency repair spend reallocated to planned renewal.
  • ↑ 3× faster capital-case approvals at council level.
/I.06 — Life Sciences

Production reliability without breaking validation.

Regulated assets, calibration, utilities, production reliability. Where every change is a change-control package and downtime translates directly to patient impact.

What we hear
  • Calibration backlogs grow; deviations follow.
  • Utilities reliability is treated as a given until it isn't.
  • Maintenance data and QMS data tell different stories about the same event.
Where we focus
  • Calibration interval optimization within validated guardrails.
  • Utilities reliability analytics on HVAC, water, and clean-utility systems.
  • Integrated maintenance and quality intelligence with audit-grade lineage.
Signature outcomes
  • ↓ 34% calibration backlog without revalidation.
  • ↓ 26% deviations linked to utilities reliability events.
  • ↑ 100% audit traceability from work order to QMS record.
— 06 / 90-Day Launchpad

Start with one asset class.
Prove the model.
Scale the framework.

Our Reliability Launchpad delivers a measurable AI use case in 90 days — fixed-fee, milestone-based, with an executive roadmap for enterprise scale. No abstract proofs of concept.

01 — Your details
02 — Project scope
Direct line +1 (365) 275-2362
Head office 264 Vaughan Road
York, ON  M6C 2N1
12-week launchpad roadmap
Wk 1–2 Discovery & data readiness
Asset selection, data audit, success metrics, stakeholder alignment, and a clear definition of done.
Wk 3–6 Model build & validation
Feature engineering, model training, holdout testing, and reviewer sign-off against agreed accuracy targets.
Wk 7–10 Production pilot
Live operation in a single plant, KPI tracking, user workflow integration, and on-the-ground change management.
Wk 11–12 Executive roadmap
Business case, scale plan, capital sequencing, and an executive-ready roadmap to roll out across sites and asset classes.
What you walk away with
  • 1 A working AI use case in production on one asset class
  • 2 Verified ROI signed off by your Finance team
  • 3 A costed roadmap to scale across the enterprise
  • 4 Everything we built — yours to keep, scale or not
Fixed fee 90 days · milestone-based