AI Usage Framework · Method · Responsibility
AI usage framework.
FlashInsight is a decision-support tool for marketing teams. It delivers structured early signals to help you decide sooner — but it does not replace your professional judgment, nor a full field study when the stakes and the budget call for one.
1. What the AI delivers
The results (insights, summaries, verbatims, scores) are produced by probabilistic models and simulations calibrated against the target audience. They are useful projections to explore, compare and prioritize earlier in the decision cycle.
2. What the AI does not guarantee
The outputs are not factual truths and may contain errors or biases. FlashInsight does not guarantee any commercial, marketing, financial or strategic outcome. The method frames the rigor of the protocol — not the performance of the choice that follows.
3. Your usage commitments
You agree to read the results critically before any decision. You remain responsible for compliance (legal, regulatory, sector-specific) and for how the insights are used in your business.
4. Our commitments
We maintain a security and confidentiality framework, and we make explicit that the content is AI-generated. Files you upload (stimuli, briefs, context documents) are processed within the scope of the service.
5. Responsibility for decisions
Decisions made based on the results are yours. FlashInsight cannot be held responsible for operational, strategic or commercial choices made on that basis.
6. Acceptance
By launching a study or a run on the platform, you accept this AI usage framework.
Our commitments on simulated responses
Our studies rely on simulated respondents: profiles built from public statistics, not real people who were interviewed. The method has value and it has limits. Here is what we commit to.
1. We will never present a simulated response as a human one.
Every deliverable states that it comes from simulated respondents. We use no wording that would suggest a survey of real people.
2. We do not replace direct measurement.
When a decision requires asking real people, real people should be asked. Our method is for exploring, screening and preparing — not for deciding in place of fieldwork. We say so to clients, including when it costs us the work.
3. We publish our validation results, with their limits.
We regularly measure the gap between our simulated populations and real human data. We publish those measurements. We also publish what does not work: a method whose failures are never shown cannot be checked.
4. We state what was simulated, and from what.
Which population, which statistical sources, which reference date, how many respondents — so that a reader can judge the scope of the result for themselves.
5. We state what the method should not be used for.
Our results are read as comparisons and directions: which concept comes ahead of which, in what direction, for which group. They are not read as absolute levels, nor as a prediction of what one particular person will do. That limit appears in the deliverable itself, not only in a contract.
These commitments follow the standard Gallup published in May 2026 on the use of simulated responses. We adopt them because they seem to us the right level of requirement, and we say where they come from.
7. Pedagogical FAQ
Does FlashInsight replace a research firm?
No. FlashInsight is built to iterate fast and surface a first level of structured signal — between instinct and the full study. For high-stakes decisions, in budget or reputation, a complementary field study is still recommended.
Why probabilistic results?
Because AI simulates likely behaviors, not certain facts. The results help you decide, but they do not guarantee future performance. We work on relative gaps — which concept wins — more than absolute scores.
Who is responsible for the final decision?
You. The platform sharpens your judgment — it does not replace it. Business validation and operational choices remain yours.
How to use AI insights well?
Use them as a tool: cross-check them with your context, your internal data and — when the stakes justify — complementary field validations. Method over Magic.
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To discuss the scope of a project, or for any question on this framework: flashinsight.io