Data quality is usually handled at the end of a study: a cleaning pass that removes speeders, straight-liners, and obvious nonsense. By then the damage is done, because the quota is full and there is no time to replace the bad interviews.
Opinio Flow moves that check into the conversation itself. Every response is scored live on relevance (is this answer actually about the question?), completeness (was the point explored or skimmed?), voice authenticity (is this the same person who joined, without storing a biometric profile?), and sentiment (how is the tone shifting as the conversation unfolds?). Fraud and bot signals and duplicate-respondent checks run alongside.
Because scoring happens in real time, a weak conversation is flagged while the study is still in field and can be replaced. Every conversation also carries an audit trail, so a stakeholder who questions a finding can see exactly where it came from.
Trust is not something you add to a study at the end. It has to be built into every response.