Company and trust
What we will claim, what we will not, and how to check us: replication accuracy defined precisely, the boundaries of simulated evidence, and how engagements actually run. Fewer articles live here than anywhere else, deliberately. Trust pages should be short and verifiable.
- Building an AI Governance Layer for Market Research
A research leader who lets AI-assisted output move straight into a stakeholder deck is making a governance decision, whether or not anyone wrote it down.
- How much validation does a research decision need?
A buyer weighing causal experimentation against incumbent market research asks two questions: does this method answer "why," and how much validation does this decision need before…
- AI Research Ethics: A Practical Guide for Simulated Respondent Research
Presenting simulated-respondent findings to a board, an investor, or a launch committee is a disclosure decision, not just a data decision.
- 5 Structural Signals a Research Team Will Deliver Fast, Auditable Causal Experiments
A research, product, or strategy leader picking a vendor for a high-stakes causal experiment buys more than a method: a team's ability to design the test, interpret the result…
- Subconscious.ai FAQ: What a Causal Behavioral Experiment Can and Can't Tell You
Subconscious.ai runs controlled causal experiments on simulated populations so a team can estimate which product, pricing, or messaging action is likely to change customer…