PRODUCT COMPARISON
Compare synthetic research tools
Compare product uses, methods, validation evidence, data sources, access and pricing. Start with Aaru and Simile, or choose two or three other products.
Product records: 6 September 2026. Method and evidence sources linked below.
| Compare products | TolunaHarmonAIze Boost | FairgenBoost |
|---|---|---|
| Product category | Sample augmentation | Sample augmentation |
| Product | HarmonAIze Boost | Boost |
| Overview | Post-fieldwork synthetic augmentation for smaller or hard-to-reach survey groups. | Synthetic expansion of existing survey samples for deeper subgroup analysis. |
| Data grounding | Toluna defines Boost as amplifying patterns in existing collected data, rather than recruiting new respondents. | The provider positions Boost as a hybrid tool working from existing research samples. |
| Access | Research engagement | Contact sales |
| Pricing | Discuss scope with provider | Discuss scope with provider |
| Research method | Toluna defines HarmonAIze Boost as a tool that amplifies patterns in existing data to extend analysis of hard-to-reach or low-incidence segments, without additional data collection. | Fairgen says Boost uses patterns in an existing survey to generate augmented respondents that follow the survey structure, including logic such as skips, piping and multi-selects. |
| Validation evidence | No product-specific performance result in the sources listed here. | Reported brand-lift pilot: Fairgen reports a pilot using Boost with real brand-lift survey data processed through Google's Ads Data Hub. The supplier says the pilot covered 52 study cuts across five industry verticals and examined recoverable statistical precision through augmentation. This is Fairgen's own account of a specific pilot. It should be read as a scoped augmentation study, not as a general guarantee for all questionnaires, segments or model configurations. |
| Documented scope | Toluna defines Boost as amplification of patterns in an existing dataset without additional collection. The suitability of an augmented result therefore remains tied to the original fieldwork, its sample and its measures. | Boost augments patterns in collected survey data. Generated records are not additional people interviewed. |
| Method and evidence sources | ||
| Primary source | Provider documentation | Provider documentation |
Product comparisons
- Aaru vs Simile
Both describe population simulations. Aaru frames scenarios around a decision and stated conditions; Simile documents a question-level confidence model alongside its simulated action distributions.
- Fairgen Boost vs Toluna HarmonAIze Boost
Both work with a survey that has already been collected. Fairgen describes augmenting survey segments while preserving questionnaire structure; Toluna defines Boost as amplifying patterns after fieldwork.
- Qualtrics Synthetic Panels vs Synthetic Users
Qualtrics generates synthetic responses within its survey distribution workflow. Synthetic Users organizes audience-defined personas, projects and studies, with interviews, surveys and developer API access.
- Fairgen Twins vs Ipsos PersonaBot
Fairgen Twins supports structured studies and follow-up conversations with modeled respondents. Ipsos PersonaBot offers conversational access to personas from an existing segmentation study.