Should you build or buy Asset Investment Planning (AIP) & Capital Portfolio Management?

Asset investment planning software helps utilities decide which capital projects to fund, using a configurable value framework that scores safety, reliability, and environmental outcomes against cost. It produces the long-range capital plans and audit trails that utilities present to regulators to justify rate cases.

Could our planning team build its own asset investment optimizer instead of buying Copperleaf or DIREXYON? The evidence says not yet. No named utility documents a wholly self-built AIP in production, the credible examples are hybrids around a commercial engine, and the regulatory defensibility of the optimizer's audit trail is part of what you are buying. Build your risk models and data pipeline; buy the optimization and evidence layer.

Build it, buy it, or bridge?

⚒ Build it
✓ Buy it
➔ Bridge
Cost shape
No public case shows an in-house build undercutting a vendor subscription once data cleanup and audit-trail work are priced in
Vendor pricing is quote-based and scales with utility size and the depth of the value framework configured
Buy the optimization and value-framework layer; build your own risk models and data pipeline underneath it
Time to value
No named utility has taken a self-built optimizer from raw data to a defensible rate-case filing
Vendor platforms ship a configurable value framework a utility adapts to its own risk appetite relatively quickly
Feed vendor-configured optimization with your own asset condition data as that data matures
Differentiation captured
You'd own the risk models feeding the optimizer, which is real value even without owning the optimizer itself
The optimizer's audit trail and regulatory evidence packaging is part of what a rate case actually needs
Own the risk and condition models; let the vendor's evidence packaging carry the regulatory weight
AI feasibility today
No AI tool built a self-built AIP core; PG&E's SNAP still wraps a commercial optimizer
AI shows up as scenario generation inside vendor platforms, refining the optimizer rather than removing the need for one
Use AI-assisted risk modeling in your own data pipeline while the vendor's optimizer runs the prioritization math
Who it fits
No utility has documented a wholly self-built AIP core in production at any scale
Regulated utilities of any size that need a defensible, auditable capital planning process for rate cases
Utilities with strong internal engineering wanting to own risk models on top of a vendor optimizer

When building makes sense

There isn't a clean build case for asset investment planning, and the evidence is thin enough that it's worth naming directly. The most substantial named example, PG&E's System Needs Analysis Platform, is built on Palantir Foundry to aggregate and visualize asset risk across wildfire and reliability categories, but it's integrated with IFS Copperleaf rather than replacing a commercial optimizer, which makes it a hybrid, not a self-built alternative. What a utility can build, and what's worth building, is the risk model and data pipeline that feeds an optimizer: asset condition scoring, failure probability models, and the data cleanup that makes any of it trustworthy. That work is genuinely utility-specific and doesn't require buying anyone's proprietary optimization engine outright. What isn't credible, based on what's documented, is replacing the optimizer itself along with the regulatory evidence trail it carries, since no utility has shown that's been done independently.

When buying makes sense

Buying earns its place here because of what a rate case actually demands: a defensible, auditable process for deciding which capital projects get funded, not just a working spreadsheet. Copperleaf's value framework, integrated into platforms like PG&E's Palantir Foundry-based SNAP for aggregating wildfire and reliability risk, exists because regulators expect a specific kind of evidence trail, and building that credibility from scratch inside a utility with no prior track record is a hard sell in front of a rate commission. Vendors including DIREXYON and Brightly compete on long-horizon simulation and asset-condition risk ranking rather than the underlying optimization math, which is itself fairly standard. The honest split is to buy the optimization and evidence layer while building your own risk models and asset condition data underneath it, since that's where a utility's actual planning quality lives, and where the vendor isn't offering anything more defensible than what your own engineers already know about your assets.

The desk read

Build-versus-buy analysis for Asset Investment Planning (AIP) & Capital Portfolio Management is being written. In the meantime, the framework that drives every B4 call is on the B4 Index page.

Representative vendors Brightly Asset Investment PlanningCopperleaf Asset Investment PlanningCopperleafDIREXYONBrightly + 1 more, listed in the full index

Frequently asked

Has any utility built its own asset investment planning system instead of buying one?

Not cleanly. PG&E's System Needs Analysis Platform runs on Palantir Foundry to aggregate and visualize wildfire, reliability, and other asset risk, but it integrates with IFS Copperleaf rather than replacing a commercial optimizer, which makes it a hybrid rather than an independent build.

What is a utility actually buying when it licenses an AIP platform?

A configurable value framework and an audit trail that regulators recognize, not just optimization math. PG&E uses its Copperleaf-integrated platform specifically to aggregate and visualize risk across categories like wildfire and reliability for planning and rate-case purposes.

What part of asset investment planning is worth building in-house?

The risk models and data pipeline: asset condition scoring, failure probability, and the data cleanup that makes any optimizer trustworthy. That work is genuinely utility-specific and doesn't require replicating a vendor's proprietary optimization engine or its regulatory evidence trail.

What are the main asset investment planning vendors?

Representative vendors include Brightly Asset Investment Planning, Copperleaf Asset Investment Planning, Copperleaf, DIREXYON, Brightly. B4 Pro includes the category score and the full vendor list.

The B4 Index scores every software category on two axes, strategic differentiation and AI feasibility, to classify it Build, Buy, Bridge, or Beware. See the full methodology.