About the role
We are looking for a small number of expert practitioners for a paid 30-60 minute product feedback interview. The client is building AI technology to help detect when people in high-stakes conversations may be relying on scripts, coaching, AI tools, generic answers, or overstated expertise.
This is not a job application. This is not for general industry opinions. We only want people who have personally evaluated authenticity, quality, credibility, compliance, provenance, or first-hand knowledge in one of the tracks below.
Please do not apply if your experience is mostly adjacent, junior, academic-only, agent-only, administrative, or theoretical. You should be able to give concrete examples from work you personally owned or reviewed.
Tracks covered by this shared form: Expert Network / Primary Research; Financial Data / Transcript Data; Investor Relations; Qualitative Research; Academic Research; Contact Centre Quality & Compliance.
Selected advisors may be invited to a short 10-15 minute fit call, then a paid 30-60 minute product feedback interview scheduled around them. Payment is confirmed on selection.
What you'll do
Share first-hand product feedback from the exact track where you have direct practitioner experience.
Explain how authenticity, credibility, quality, compliance, provenance, first-hand knowledge, scriptedness, AI assistance, or overstated expertise are evaluated in your field.
Walk through concrete examples where you personally checked whether a person, answer, source, dataset, call, transcript, or claim was credible and first-hand.
Describe the tools, workflows, scorecards, audit methods, quality signals, or review processes used today, including where they fail.
Advise what a new AI detection or verification approach would need to prove before practitioners in your field would trust or act on its flags.
Must have
Direct hands-on experience in one of the listed tracks, not merely adjacent exposure.
Personal experience evaluating whether people, answers, sources, data, claims, or expertise were authentic, first-hand, scripted, AI-assisted, generic, or overstated.
Concrete examples from work you personally owned, reviewed, QA'd, audited, moderated, investigated, or escalated.
Enough seniority or ownership to explain real workflows, tools, failure modes, and decisions, not only individual task participation.
Comfort with a short fit call and, if selected, one paid 30-60 minute product feedback interview.
Nice to have
Ownership of QA, compliance, research, data quality, expert screening, investor communications, transcript review, fieldwork, or audit workflows.
Experience with regulated, high-stakes, or decision-critical conversations where scriptedness, coaching, AI assistance, or overstated expertise creates risk.
Experience using or designing scorecards, calibration workflows, evidence checks, panel validation, transcript QA, dataset lineage, reconciliation, disclosure review, or compliance audits.
Ability to explain what signals would be useful, what would create false positives, and what proof would be needed before a team trusted the product.