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Venturalítica
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Venturalítica

The team decides how to treat each risk

The team declares the system’s context, describes its data with Croissant metadata and defines controls to treat its risks. Froga collects evidence from runs and the artifacts they produce to complete the technical documentation.

Declarations and observations

Declared by the team

purpose of the system
what it is for and whom it affects
applicable standards
the ones the team declares
description of the data
Croissant metadata: the dataset’s origin, structure and conditions of use

The description records what is declared; it does not verify the data itself.

Collected from the run

Description of the model
It draws on the components, artifacts and results available from each run. Its scope depends on the evidence collected.

The team decides how to treat each risk

The team identifies and assesses each risk and decides how to treat it: reduce it, accept it with justification, avoid it or transfer it. To put that treatment into practice, it defines the necessary controls and their acceptance criteria. Results and evidence inform the review of the treatment and reassessment of the remaining risk.

Each control specifies what is checked, the criterion and the supporting evidence. For a numerical check, the acceptance criterion includes a threshold.

The team defines separately how each result affects whether work continues.

The cycle connects identification, analysis, evaluation, treatment, checking and review of residual risk, then starts again. Each stage is documented. The team decides on residual risk.
  1. Identify
  2. Analyse
  3. Evaluate
  4. Treat
  5. Check
  6. Review residual risk

Fictional example · simulated figures

RSK-DEMO

Defects that escape inspection

Declared impact
High
Declared likelihood
Possible

Path to harm

  1. One part type is underrepresented in the data.

  2. The model detects its defects less reliably.

  3. The part moves through the process without additional review.

Consequence
A defective part reaches assembly and compromises product quality.
Risk treatment
Reduce. Extend validation across part types and capture conditions; review uncertain cases before releasing the version.

Treatment controls

Defect detection rate. Each control retains its criterion, result and evidence.

  • C-01Overall detection

    Meets the criterion

    Acceptance criterion
    ≥ 95%
    Simulated result
    96%

    Evidence: Overall evaluation of the test dataset.

  • C-02Detection by part type · worst group

    Does not meet the criterion

    Acceptance criterion
    ≥ 90%
    Simulated result
    82%

    Evidence: Evaluation broken down by part type.

  • C-03Detection under adverse lighting

    Not measured

    Acceptance criterion
    ≥ 90%
    Simulated result
    Not available

    Evidence: These conditions have yet to be evaluated.

Scale 0–100%. Dashed line: threshold. Solid marker: simulated result. No marker: no measurement.

Residual risk
Awaiting reassessment
Decision configured for this example
Hold the version until the failing control is resolved and the missing measurement is completed.

Fictional visual inspection case: criteria and results are simulated, not client data or recommended thresholds. A passing control alone does not demonstrate that the risk has been treated.

Automated checks remain distinct from documented human reviews and evidence that does not yet support a conclusion. Recording a human assertion does not turn it into a measured or validated check.

What changes for your team

Your team keeps deciding the risks, the controls and the thresholds. Every run keeps the evidence in the technical documentation up to date.

If it fits so far, the next step is a conversation.

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