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Input data generation

Assumption assistance

Speed up input without sacrificing consistency

This module fills the gaps in your simulations (maintenance, vacancy, insurance, repairs) with realistic, explained assumptions, matched to the asset type and the Quebec market.


Objectif
Saisie rapide
anti-blocking
Method
Valeurs guidées
by asset type
Comparaison
Scenarios
Conservative / Base
Control
Validation manuelle
toujours requise
Règle d’or
The AI proposes consistent assumptions. You validate the ones that match your reality and your risk tolerance.

Types of data generated

The proposed assumptions serve as the basis for more robust simulations.

Entretien & réparations

Recurring and unexpected budgets tailored to the age and type of building.

  • Entretien annuel moyen
  • Recurring + unexpected
  • Impact on long-term cashflow
Vacance & rotation

Assumptions based on rental market tightness and tenant type.

  • Estimated vacancy rate
  • Average turnover time
  • Sensibilité en stress test
Dépenses récurrentes

Coherent, standardized expense grid.

  • Assurances
  • Gestion / administration
  • Services & contracts
Scénarios multiples

Comparison to measure project robustness.

  • Prudent
  • Central
  • Optimistic

Mini-formulaire (prototype)

Enough to generate initial assumptions.

Generate via AI Coach
To wire up: assumption persistence, change traceability, version comparison.

Why it is critical

Bad assumptions create false decisions. This module reduces arbitrariness and improves comparability between projects.

It also serves as the basis for the stress tests and the AI recommendations.

Run the stress tests

Better inputs, better decisions

Consistent assumptions are the foundation of robust, comparable simulations.