FAQ
How should a CRE team use this article?
Use it as a checklist for the questions to ask during underwriting, not as a substitute for source-backed deal review. The final model still needs document citations, market checks, review states, and clear assumption ownership.
Where does Cactus fit in this workflow?
Cactus reads deal-room materials, checks assumptions against market context, surfaces conflicts, lets users approve the facts that drive the model, and preserves the logic as Proprietary Memory for the next deal.
A CRE-native comparison of Cactus and IntellCRE focused on extraction, market checks, source trails, model output, review controls, and defensible assumptions.
The old way to compare CRE software was to line up feature claims and pick the one with the cleaner interface. That is not enough anymore. Underwriting software has to prove that the number in the model can be traced back to a source, challenged against market evidence, reviewed by a human, and reused by the firm later.
That is the right frame for Cactus versus IntellCRE. The question is not which tool says "AI" more loudly. The question is which workflow can take a messy deal room and produce assumptions that survive partner, lender, client, or IC review.
What to compare
- Document extraction: Can the platform read OMs, rent rolls, T-12s, leases, PDFs, spreadsheets, and customer templates without turning the process into manual re-entry?
- Market checks: Can rents, expenses, sales comps, growth targets, tax risk, insurance risk, and submarket context be checked against current market intelligence?
- Conflict handling: Does the workflow show when the OM, T-12, rent roll, leases, and comps disagree?
- Assumption control: Can users approve, reject, override, and explain the numbers that drive the model?
- Output path: Can approved work move into Excel, Cactus models, memos, lender packages, BOVs, OMs, IMs, and presentation outputs?
- Firm memory: Does the work compound into reusable firm context, or does it disappear into another one-off file?
Where Cactus is different
Cactus is built around the underwriting control layer. It reads the deal package, structures the facts, checks assumptions against market intelligence, surfaces conflicts, and lets users decide what drives the final model. It can support customer Excel models or Cactus models, then preserve approved facts, templates, comps, assumptions, and reviewer decisions as Proprietary Memory.
That matters because most underwriting risk does not announce itself as a bad formula. It shows up as a rent assumption that was copied without support, an expense line that was normalized incorrectly, a sales comp that does not match the submarket, or a reviewer decision that never made it back into the next deal.
What to verify for IntellCRE
For IntellCRE or any competing underwriting tool, verify the workflow with your own files. Public feature pages rarely answer the hardest questions: what happens when sources conflict, how assumptions are approved, whether customer Excel templates can be populated, how market data is sourced, and whether prior firm logic can be reused.
- Ask for a live extraction from your own OM, rent roll, and T-12.
- Ask how conflicts are flagged when source documents disagree.
- Ask what market data categories are live, what is planned, and what requires customer-provided sources.
- Ask whether assumptions carry citations, timestamps, confidence states, and reviewer ownership.
- Ask how the output returns to your actual underwriting model.
Bottom line
Cactus should be evaluated as ARGUS-grade underwriting intelligence with a source-backed workflow around the model. If another platform can match that on real files, it deserves attention. If it cannot show the evidence trail behind the number, it is not ready to own a serious underwriting process.
How Cactus turns this into defensible underwriting
A comparison only matters if it predicts which workflow can stand up in diligence. Cactus is built for teams that still need ARGUS-level analysis, but want source-backed extraction, premium third-party market intelligence, public records, review controls, and reusable firm memory around every assumption.
- Extract relevant facts from OMs, rent rolls, T-12s, leases, PDFs, spreadsheets, and customer templates.
- Check rents, expenses, growth targets, cap rates, sales comps, and site context against market intelligence from premium data providers, public records, and firm history.
- Surface conflicts, confidence states, reviewer comments, and assumption overrides before the model becomes the memo.
- Populate Excel or Cactus models, then store approved facts, templates, comps, and decisions in Proprietary Memory for the next deal.
The point is not to make the model less sophisticated. The point is to make the source, market check, assumption owner, review state, and output path visible before the number reaches a partner, lender, client, or investment committee.
Defensible underwriting
Defend every number before it reaches IC.
Cactus gives CRE teams ARGUS-grade underwriting intelligence with document extraction, market checks, source trails, reviewable assumptions, Excel-ready outputs, and Proprietary Memory around the workflow.
- Rent rolls, T-12s, OMs, comps, and assumptions live in separate files.
- Market evidence gets copied into the model without a durable source trail.
- Reviewer decisions disappear after the memo, email thread, or spreadsheet version changes.
- Extract deal facts from OMs, rent rolls, T-12s, leases, PDFs, spreadsheets, and customer templates.
- Check rents, expenses, growth targets, sales comps, and other assumptions against market intelligence.
- Populate Excel or Cactus models and preserve approved logic as Proprietary Memory.
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