Asset management on Built AI · Continuous variance & risk

Block 37 · Variance & covenants

Live · actuals reconciled 2m ago

NOI vs plan

Covenant watch forecast breach

High DSCR 1.20× test Aug 1 · forecast 1.18× at current trend

Variance drivers explained

Continuous variance and covenant monitoring. The Aug 1 DSCR breach is forecast before the test, every driver traced to its GL line, lease or notice.

Reconciling actuals against plan against comp, by hand, every quarter

The first two weeks of every quarter disappear into reconciliation, walked by hand across every asset until the team can explain why NOI came in light.

Today vs. with Built AI

When the variance is ready to act on...

The deeper issue

The knowledge required to read a portfolio well does not scale by hiring...

The shift

Variance computed as it happens, explained in plain English, traceable to source

Built AI binds the systems you already run, your accounting, your Argus, and underwriting models, your leases, and loan documents, into one normalized knowledge graph.

Continuous variance:
Reconciliation runs the moment actuals land, not two weeks after close.

  1. Actuals post
  2. Bridge reconciled
  3. Variance explained
  4. Drill-through

Covenant Watch, before the test date

Covenant Watch re-tests DSCR, debt yield, and LTV on every refresh against the actual covenant language...

Lease intelligence

The platform reads every lease in the portfolio into structured terms and keeps a live view of rollover exposure.

What you gain

Four changes to the seat

  1. The variance pack writes itself: On every actuals refresh, the NOI bridge is built, drivers are isolated, and the narrative is drafted.
  2. Covenant breaches surface before the test date.
  3. Lease and rollover risk become a live view.
  4. The portfolio answers questions in minutes.
The work Today With Built AI
Variance analysis Built by hand, two weeks after close, stale on arrival Continuous, computed as actuals land, narrative drafted
The NOI bridge Re-keyed into a spreadsheet each period Built automatically, every driver traced to source
Covenant testing Discovered when the lender's certificate is due Forecast before the test date with cure options
Lease rollover Reconstructed from PDFs when someone asks A live view across the portfolio, always current
Portfolio questions Two days reconciling five systems by hand Answered in minutes by traversing the graph
Where risk is found Late, reactively, after the quarter turns Early, the day the trend bends

The case for an AI-native operating model, in numbers

The strongest argument is not a headcount cut, it is capacity...

The illustrative team and cost model

Portfolio size 150 properties.
Annual team-cost saving ~$3.03m

Sources. Capacity figures (16 vs 13 properties)...

It sits on top of Yardi, Argus and your model

An orchestration layer that reads your systems of record and writes back only on approval.

Human in the loop

Your judgment stays the authority. An agent that can silently revise a covenant test or post a number...

"Built AI is already shaping how we think about asset management, surfacing asset-specific risks and opportunities in minutes." - Carlos Olea, CFO, Howard Hughes Holdings (NYSE: HHH)

See continuous variance on your own portfolio.

Bring a fund, an asset, and its actuals, and watch the platform build the NOI bridge, forecast the covenants and surface the rollover risk, every number traceable to source.