TenePass Evaluation Engine uses a hybrid evaluation engine that combines AI assisted preprocessing with certified human review. This approach keeps the evaluation fast, consistent, and fair while protecting privacy.
AI Assisted Document Preprocessing
When a renter uploads documents, TenePass runs a series of automated checks to prepare the case for the evaluator.
The AI layer performs tasks such as:
- Extracting names and matching them with the applicant
- Detecting expiration dates
- Checking if documents fit the required time window
- Identifying missing pages or inconsistencies
- Flagging anomalies or incomplete data
- Flagging fraudulent patterns
These automated checks help reduce human workload and prevent common mistakes.
Issue Detection and Revision Loop
If AI detects a problem, the system notifies the applicant to correct or resubmit the affected document. This ensures that the evaluator receives a clean, consistent file set.
If everything looks good, the case moves directly to manual review.
Structured Manual Evaluation
A trained professional evaluator reviews the prepared case through a structured interface. They never type or write free text. Instead, they select predefined items inside decision groups, each mapped to scoring rules set by administrators.
This ensures:
- Consistency across evaluators
- No subjective interpretation
- A fully auditable scoring trail
- Clear mapping between documents and scoring decisions
Evaluators only see the applicant’s documents. Landlords and agents never see these files.
Weighted Scoring Engine
TenePass uses a structured evaluation model built from two core building blocks: evaluation steps and decision groups. These elements create a consistent, transparent, and human reviewed scoring process while using AI for preprocessing support.
What Are Evaluation Steps
Evaluation steps are the main sections of the TenePass scoring model. Each case type in TenePass has their own dedicated evaluation steps and each step represents one dimension of rental trustworthiness.
Examples include:
• Financial strength
• Professional stability
• Rental history
Each step has:
• A predefined weight
• Linked submission data
• One or more decision groups
These weights always add up to 1.0 (100%). The engine uses this structure to calculate a final rating on the 0 to 10 scale.
The Role of Decision Groups
Decision groups sit inside each evaluation step. Every decision group contains fixed options the evaluator must pick from.
Example of available options inside Income vs. rent decision group:
• Income covers rent comfortably > 10 points
• Income covers rent with limits > 6 points
• Income does not cover rent > 0 points
Each option has a fixed numeric point. The maximum points in a each decision group is always 10.
There is no free writing or subjective input. Evaluators always choose one structured option. This makes the evaluation fully auditable and consistent.
During review, the evaluator goes step by step and selects one option per decision group. Their selections add up inside the step and reflect the applicant’s strength in that category.
How the Final Score Is Created
Each evaluation step has its own weight.
The points selected inside that step are calculated according to that weight, so more important steps influence the final score more strongly.
All weighted step results are combined to create a final score on a 0 to 10 scale.
The standard TenePass boundaries keep the result fair and comparable across all applicants.
Dynamic Affordability Adjustment (DAA)
If the renter requests a score for a different rent amount, the engine applies the Dynamic Affordability Adjustment formula. This adjusts the score proportionally without redoing the entire evaluation. The evaluator’s original rating always stays intact.
Why TenePass Evaluation Engine Is Better Than Traditional Screening
Traditional screening uses unstructured documents and unstructured human interpretation.
TenePass removes both problems by:
• Using AI to clean and verify documents before human review
• Guiding evaluators through tightly structured steps
• Preventing free text scoring
• Keeping the scoring logic fixed and auditable
• Maintaining privacy by hiding documents from landlords
This creates a trusted, equal, and fair evaluation system for all renters.
Frequently Asked Questions
Where do the TenePass evaluation steps come from?
TenePass uses the same core factors that most landlords, rental agents, and professional screening solutions already check.
These are the most commonly used and widely accepted areas for evaluating rental trustworthiness, such as financial strength, professional stability, and rental history.
Why do evaluation steps have different weights?
Each step has a predefined weight because some factors matter more than others in real rental decisions.
These weights reflect what landlords and agents consider most important when choosing a trustworthy renter. The weighting makes the final score fair, realistic, and aligned with real world expectations.
How is the TenePass score fair?
The TenePass score follows one standard method for every renter.
Everyone is evaluated through the same steps, the same decision groups, and the same scoring rules.
This gives landlords and agents a clear comparison across all applicants and removes subjective judgment.
Who creates the evaluation logic?
The logic is designed by TenePass using data from the rental market, industry standards, and feedback from property professionals.
Evaluators do not set or change the logic. They only follow the structured system.
Can evaluators add their own opinions?
No. Evaluators cannot write comments or create their own scoring rules.
They only select predefined options inside each decision group, which keeps scoring consistent and auditable.
Do landlords see my documents?
No. Only evaluators see documents.
Landlords and agents only see your final rating and certificate metadata.
Does AI decide my score?
No. AI only helps with document checking.
Your score is always decided by a trained human evaluator using structured decision groups.
