A focus group for new AI features
Show real, verified people what a new AI feature does before you ship it, and get their read in minutes.
How it works for this decision
Your agent sends
{
"question": "Would you trust this answer?",
"context": "A new AI travel assistant replied: Your flight is delayed. I have rebooked you on the 6:40 am flight tomorrow and cancelled your hotel for tonight.",
"options": [
"Yes",
"Not sure",
"No"
],
"verifiers": 3
}A verified person sees
Would you trust this answer?
A new AI travel assistant replied: Your flight is delayed. I have rebooked you on the 6:40 am flight tomorrow and cancelled your hotel for tonight.
You get back
{
"answer": "Not sure",
"agreement": 0.667,
"answers": 3,
"votes": {
"Yes": 1,
"Not sure": 2,
"No": 0
}
}The result shown is an example. Try answering the task yourself.
Why a human check
Teams test new AI features on themselves and a few friendly users. Real people read things differently: a reply that sounds helpful to the team can come across as cold, confusing or wrong.
Several independent, ID verified people answering the same question about the same output give a quick, honest signal, without recruiting a panel or waiting a week.
- Ask one narrow question per task, with clear options.
- Send the same output to more people (up to 9) for a steadier read.
- Compare two versions of a feature by sending each as its own task.
Questions
Is this a replacement for user research?
No. It is a fast first read before launch. Use it to catch the obvious problems, then talk to your users.
How do I start?
Get your API key at plures.si. Start with your own team: the first 50 decisions each month are free. Add credit when you want ID verified people on the rest, live right away.
More use cases
- Launch and securitySecurity review for risky agent actionsIs this message trying to get the agent to break its rules?Looks like an attackNormal request3 of 3 verified people agreedHave people check requests that look like prompt injection, social engineering or abuse before your agent acts on them.See how it works
- CustomersCatch upset customers your support agent misreadsIs this customer upset?YesNo3 of 3 verified people agreedHave people check tone and intent before an AI support agent closes, refunds or escalates a ticket.See how it works
- CustomersVerify refund and dispute decisions before money movesWhat is this customer asking for?Full refundReplacement partInformation only3 of 3 verified people agreedAsk verified people whether a refund request is legitimate and what the customer is actually asking for.See how it works