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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
Quick entry
anti-blocking
Method
Guided values
by asset type
Comparaison
Scenarios
Conservative / Base
Control
Validation manuelle
always required
Rule of thumb
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.

Maintenance & repairs

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

  • Average annual maintenance
  • Recurring + unexpected
  • Impact on long-term cashflow
Vacancy & turnover

Assumptions based on rental market tightness and tenant type.

  • Estimated vacancy rate
  • Average turnover time
  • Sensitivity under stress test
Recurring expenses

Coherent, standardized expense grid.

  • Assurances
  • Management / administration
  • Services & contracts
Multiple scenarios

Comparison to measure project robustness.

  • Prudent
  • Central
  • Optimistic

Mini form (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.