See It Work
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See It Work
SYSTEM: OPERATIONAL OT/IT CONNECTORS: 150+ AUTONOMOUS OPERATION: 15+ DAYS GOVERNED AUTONOMY: ENFORCED AUDIT TRAIL: IMMUTABLE INDUSTRIES: ASSET-INTENSIVE & MISSION-CRITICAL DEPLOYMENT: 3-6 MONTHS VIA APEX CONTROL LOOPS: 3,400+ SYSTEM: OPERATIONAL OT/IT CONNECTORS: 150+ AUTONOMOUS OPERATION: 15+ DAYS GOVERNED AUTONOMY: ENFORCED AUDIT TRAIL: IMMUTABLE INDUSTRIES: ASSET-INTENSIVE & MISSION-CRITICAL DEPLOYMENT: 3-6 MONTHS VIA APEX CONTROL LOOPS: 3,400+
Available WATER-UTIL-ASSET-LIFECYCLE-ADV-001 AI Agent

Asset Lifecycle & Capital Planning Advisor

Turns capital planning from age-based to condition-based, typically improving capex efficiency by 15 to 25%.

Water & Wastewater Capital Planning

Target outcome · 15 to 25% improvement in capex efficiency. 5-year capex forecast accuracy from ±30% to ±15%.

Business problem

Capital planning for major plant assets — pumps, blowers, clarifiers, tanks, membranes — is typically driven by asset age, operator opinion, and reactive response to failures. The result is predictably lumpy capex: either too early (replacing assets with life remaining) or too late (failure-forced replacement at emergency premium).

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For a mid-size utility, total replacement-value asset base is typically $100M to $500M. Annual capex runs at 2 to 5% of that. Studies across water utilities consistently show that condition-based capital planning produces 15 to 25% better capex efficiency than age-based planning. On a typical portfolio that is $300K to $6M per year, depending on scale.

What it does

Integrates condition data from the predictive maintenance Advisors, usage data, maintenance history, and industry reference data.

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Produces per-asset end-of-life forecasts with confidence bands, a replacement priority ranking across the full portfolio, a 5 to 10-year capital forecast, a maintenance-versus-replace trade-off analysis, and scenario modelling for deferral decisions.

Current process vs. with AI Agent

TODAY · CAPITAL PLANNINGREACTIVE
×
Which assets to replace next yearAge-based list, operator input
×
Annual capex envelopeHistorical average with adjustment
×
Maintenance vs. replaceManager judgement
×
Board or council capital presentationAnecdotal defence

Outcomes and measurement

Capex efficiency (value per dollar)

Baseline Baseline
With agent +15 to 25%

Emergency replacement events

Baseline Site-specific
With agent 50% reduction

5-year capex forecast accuracy

Baseline ±30%
With agent ±15%

*All figures are typical ranges. Achievable range depends on existing control maturity, data quality, and site-specific conditions.

Data inputs

CMMS work order and cost history

Other

failure cause codescondition data from predictive maintenance Advisorsindustry failure-rate reference datacapex targets

asset register with installation dates and replacement values

regulatory replacement drivers

*Categories only — no tag names or system-specific field references. Exact data mapping is scoped per site.

Scoping questions

Expect these questions in a first scoping conversation. They signal engineering discipline and help narrow the template to your specific site context.

  1. What is the current asset register completeness and accuracy?
  2. What CMMS history depth is available?
  3. Are replacement values current?
  4. What is the utility's capital planning cycle?
  5. Who owns the capex envelope decision and what governance model applies?

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Get specialist advice on scoping this for your site.

Our specialists will help you understand how the Asset Lifecycle & Capital Planning Advisor fits your operations, what data you'd need, and what a scoping engagement typically looks like.

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