Capital project delivery is accelerating — most delivery models aren’t built for it.
AI is making speed to value possible at a new scale—bringing production, cashflow and benefits forward. But it won’t happen with yesterday’s delivery model. If decision loops and interfaces don’t keep up, you don’t get speed—you get churn, rework and site disruption.
No platform rollout. We work inside your existing delivery system.
What’s changing
Engineering timelines are about to collapse.
Concept select, FEED, detailed engineering and procurement will compress from years to months. The constraint won’t be producing deliverables — it will be keeping decisions, assurance, interfaces and vendors aligned fast enough to turn speed into start-up, not rework.
Late changes won’t stop — they’ll accelerate.
New technology, new regulation, and shifting requirements will keep arriving later and faster. Delivery models built on “decide everything up front and resist change” will lose. If you can’t integrate late change quickly without derailing execution, you’ll get rework, delays, and a slower path to start-up.
Projects won’t be “one and done” anymore.
In the old model, data was a by-product and ended up in the data graveyard when the job finished. In the new model, data is the asset: every FPSO, refinery, or power plant you deliver creates knowledge that speeds up the next one—faster decisions, fewer surprises, and shorter cycles.
The new constraint is the legacy delivery model.
Most project frameworks were built for governance, compliance, and control at slow speed. Now we need delivery models that provide more control—at higher speed—with better outcomes.
How we help
01
Executive Briefing (30 min)
A focused conversation to understand what’s stuck and where AI could pull value forward fastest.
You leave with: 2–3 high-leverage starting points and whether a Baseline is worth doing.
02
Fast-Cycle Baseline (2–3 weeks)
Map bottlenecks, decision loops, and dependencies using the information you already have (controls reports, decision/change logs, interface backlogs, vendor doc cycles).
You get: top friction points + recommended pilot + measures + owners.
03
6–10 week Pilot (one workflow end-to-end)
Cut cycle time on a live workflow and leave behind a repeatable way to run it.
You get: a working rhythm the team follows + measurable improvement (faster closure, fewer late surprises).
Where AI pulls value forward fastest
AI can touch dozens of workflows from FEL through start-up. We start with these six because they’re high impact and low effort: they remove waiting, reduce rework, and surface issues early using information you already produce.
Engineering & Procurement Cycle Time
Shorten the vendor doc-to-PO cycle by cutting review churn, spotting gaps early, and pushing the right exceptions to the people who can approve.
Decision Management & Change Control
AI can make the routine decisions (routing, prioritising, classifying changes) and produce decision-ready recommendations for the big calls—so the right people decide faster, with impacts and evidence already laid out.
Safety & Risk Actions (HAZID / HAZOP / SIMOPS)
AI keeps hazards, SIMOPS controls, and barriers current as the design and plan change—so safety reviews stay real, not a one-off workshop.
Interfaces & Dependencies Management
Speed up interface management by routing TQs/RFIs, tracking ageing dependencies, and escalating what’s blocking critical tie-ins before it hits construction.
Project Controls & Performance Management
AI continuously reads your project’s reports, logs, and registers, automatically routes the real exceptions to the right owners, generates decision-ready briefs, and drives follow-up and escalation—so recovery actions move in days, not weeks.
Stage Gate Pack Readiness Check
AI scans your stage gate pack for completeness, internal consistency, and missing evidence, then produces a short fix-list with owners so the gate is a decision—not a document hunt.
AI speeds up the day-to-day workflows by turning project noise into a short exception list with owners and due dates—so teams adapt fast when late change hits.
Example pilots (6–10 weeks)
Pick one workflow, prove it end-to-end, then scale what sticks.
Engineering-to-PO Cycle Time Pilot
Decision & Change Loop Reset
Interface & Dependency Burn-down
Controls-to-Action Early Warning
Also available: Value Realisation Readiness — prove what blocks start-up and ramp-up is cleared so “complete” doesn’t mean “idle.”