Harmate Simulation Mode
Simulation Mode turns an intent, a questionnaire or a business brief into a controlled test field: select personae, generate responses, read analytics signals and improve before sending anything to real participants.
Product Workflow
Simulation is not just response generation. It is a framing, execution and reading cycle that shows what will break before a questionnaire reaches a real audience.
Quick start captures the objective, profile to simulate, signals to watch and expected output before producing a usable base.
The AI assistant, templates, job descriptions and open questions help create a testable version, then rewrite what simulation reveals as ambiguous.
Indexed search, recommendations and coverage diagnostics help select relevant, diverse and contrasted personae that expose questionnaire weaknesses.
Each run keeps its identifier, checkpoints and already produced answers. You can interrupt, resume, add compatible personae and keep traceability.
Simulated answers feed Harmate views: persona answers, quality audit, AI signal, deduplicated volume, language, topics, statistics, matching, grouping and exports.
Simulated Personae
In a simulation, the panel is not decoration. Each persona carries a precise reading angle: business context, expertise level, vocabulary, resistance or expected weak signal.
Selected profiles cover the roles, contexts and maturity levels needed before launching a run.
Panel diversity exposes questions that are too vague, missing criteria and wording that is too technical.
Simulated answers become audit material: they show what to reword, remove or verify in Real Mode.
Activated Capabilities
The page should mention other features because Simulation Mode puts them into practice. Each capability below is explained through its exact role in the pre-field test.
The mode does not need a finished questionnaire. It helps turn a business intent into something that can be simulated.
The assistant generates an initial structure, rewrites weak questions and acts as a copilot after simulated answers are reviewed.
Explore AI AssistantA template or job description gives a business starting point; simulation checks whether that frame produces discriminating answers.
See TemplatesQuestion formats are tested on personae before real exposure: too vague, too closed, redundant or too technical becomes visible.
Read Open QuestionsThe power of the mode comes from the simulated panel: you need to understand which profiles test what.
Local search quickly filters profiles by context, role, signals and traits useful to the questionnaire.
Fit, diversity and coverage scoring avoids running a simulation with profiles that are too similar or poorly aligned.
A simulation can be long, partial or iterative. The product exposes state instead of hiding generation.
Produced answers are kept after each persona; you resume without losing what is already usable.
When the questionnaire remains compatible, you can enrich the panel and compare new signals with already simulated answers.
The mode gives access to Harmate analytics without confusing simulation with real collection.
You read volumes, dispersions, topics, distributions and consistency signals on simulated answers.
See DashboardsLanguage score, deduplicated volume, verbatims and quality audit show whether simulated material is usable.
Explore Language ScoreMatching views, automatic grouping and exports help compare decisions before launching the validated questionnaire.
See ExportsUse Cases
The mode is central when a bad questionnaire is costly: wasted time, poor matching, unreadable results or participants exposed too early.
You start from a job description or internal competency framework.
Decision: clarify criteria before opening collection.You simulate learners, managers and trainers on the same questionnaire.
Decision: adjust the path before involving teams.You are looking for the best candidate, pair or group from a questionnaire that is still unstable.
Decision: review weighting before using matching in real mode.You want to collect verbatims but expect noise, redundancy or overly short answers.
Decision: enrich instructions before the field.It tests a questionnaire, matching scenario or open study before involving real participants. You check questions, personae, expected answers and available analytics.
They can be configured, searched or recommended based on the questionnaire. Their role is to test blind spots, not statistically represent a real population.
Yes. The run exposes its state, keeps checkpoints and can resume without erasing already produced answers when the questionnaire remains compatible.
Yes, with simulation labeling: persona answers, audit, volume, language score, topics, statistics, matching, grouping and exports can be reviewed depending on run state.
When questions are understandable, criteria are useful, the simulated panel is contrasted enough and analytics are readable. Real Mode then validates with real respondents.
Start from an intent, compose a persona panel, control the run, analyze signals and send a stronger version to real participants.