CAM Rec Is a Knowledge Problem, Not a Math Problem

CAM Reconciliation Is a Knowledge Problem — and AI Finally Solves It

For years, CAM reconciliation has been treated like a math exercise.

Spreadsheets, allocations, percentages, true-ups — all important. But if you talk to the teams actually doing CAM Rec, the real bottleneck shows up long before the math begins.

It’s finding the answers.

The Hidden Work Before CAM Rec

Before a single number can be validated, teams need clarity on questions like:

• Who pays CAM, and who doesn’t?

• What expenses are recoverable — and what’s excluded?

• Are there caps, stops, or special provisions?

• What changed in amendments since last year?

The problem isn’t that this information doesn’t exist.
It’s that it’s buried — scattered across leases, amendments, exhibits, side letters, and prior-year assumptions.

CAM reconciliation becomes slow not because calculations are complex, but because knowledge is hard to access.

Where CAM Rec Really Breaks Down

When CAM reconciliation creates friction — internally or with tenants — it’s almost never due to a calculation error. More often, it’s because something couldn’t be quickly validated.

A clause was missed.
An amendment wasn’t surfaced.
An assumption carried over from last year went unchecked.

Teams end up spending hours digging for answers they’ve already found before, relying on memory instead of shared, source-backed knowledge.

How Prophia Changes the CAM Rec Workflow

Prophia turns lease documents into structured, queryable data — and makes that data accessible through an AI assistant designed specifically for commercial real estate teams.

Instead of treating leases as static PDFs, Prophia ingests leases and amendments, extracts the underlying data, and connects it across tenants and buildings. The AI assistant sits on top of that clean, standardized lease data, allowing teams to ask questions in plain language and get answers instantly.

For CAM Rec, that means teams can quickly ask questions like:

• Which tenants are responsible for CAM in this building?

• Are utilities or admin fees excluded for this tenant?

• Which leases have caps or expense stops?

• What changed since last year’s reconciliation?

The answers are grounded in the actual lease language — not assumptions, summaries, or spreadsheets built on memory.

From Searching to Asking

Traditional CAM workflows require teams to stop reconciling and start searching. Prophia removes that interruption.

With Prophia’s AI assistant, teams can validate CAM assumptions before running calculations, surface exceptions without manual review, and move into reconciliation with confidence that the underlying lease terms are correct.

CAM Rec becomes a process of confirmation, not discovery.

What This Unlocks for CAM Teams

When lease knowledge is instantly accessible:

• CAM prep time drops significantly

• Fewer errors and missed clauses make it into reconciliations

• Disputes are resolved faster with clear, source-backed answers

• Accounting, asset management, and leasing teams work from the same understanding

Prophia doesn’t replace CAM expertise. It removes the friction that slows experts down.

The Direction CAM Reconciliation Is Heading

CAM reconciliation will always require judgment. But it no longer has to start with a scavenger hunt through documents.

As leases become queryable and AI assistants make knowledge instant, CAM Rec shifts from a reactive process to a confident one. Teams spend less time searching for answers — and more time reconciling accurately.

CAM Rec, answered by AI, is not a future vision.
With Prophia, it’s already happening.