Property Acquisition Intelligence

Acquisition Decision Support

Turn a noisy listing feed into a diligence queue.

Each property is evaluated against hard disqualifiers, physical-condition signals, neighborhood thresholds, expected rent, rehab burden, compliance readiness, donation eligibility, and cash-purchase economics.

Listings Scanned

Current feed

Buy Candidates

Score ≥ 80

Diligence Queue

Score 65–79

Rejected

Hard fail / weak economics

Shortlisted

Saved locally

Avg Evidence

Critical diligence coverage

01 · IntakeSynthetic feed or recruiter-pasted listing copy.

02 · EvidenceExtracted facts keep source and confidence visible.

03 · EnrichmentTax, rent, market and policy inputs stay distinct from listing claims.

04 · DecisionHard gates → underwriting → evidence gaps → ranked diligence queue.

Acquisition Criteria

Adjust the operating box

Market

Strategy

Total Budget

Max Rehab

Min Rent

Min Neighborhood

Vacancy %

Maintenance %

Management %

Closing %

Hard Reject Rules

Ground rent / ground lease
Oil heat
Rehab above selected ceiling
Neighborhood below selected threshold
Total basis outside strategy budget

Recruiter tour: start with Evidence Gaps, inspect a ranked candidate, then use Analyze Raw Listing to watch unstructured copy become sourced evidence. Finish by changing the operating criteria and watching the queue re-rank.

Public-demo boundary: this build makes zero listing-provider network requests. Production intake is intentionally decoupled from the UX so source adapters can be changed without rewriting the decision workflow.

Demo Recovery

The recruiter demo hit an unexpected state.

No operational data is involved. Resetting clears only this demo’s local browser state and restores the synthetic launch dataset.

Unexpected client-side error