Remesh

Run AI-powered live focus groups with hundreds of customers at once

Intermediate
Screenshot of Remesh, Run AI-powered live focus groups with hundreds of customers at once

What is Remesh?

Remesh is a pattern recognition tool. Remesh runs AI-moderated live and asynchronous conversations with hundreds of customers or employees at once, then surfaces the themes the group collectively supports. Built for market research, employee listening and healthcare research teams that need qualitative depth without waiting weeks for a focus group report.

Remesh is an insights platform built for running qualitative research at a scale that traditional focus groups cannot reach. Instead of gathering a dozen people in a room, a team can open a live, AI-moderated conversation with hundreds of customers, employees or patients at the same time and watch the themes assemble in real time. The company positions the product as a hybrid insights tool: part live dialogue, part asynchronous response, and part automated analysis. The workflow follows three stages. In Design, a researcher builds the conversation itself, deciding what to ask and how participants will respond. In Collect, the audience is engaged, either live in a scheduled session or asynchronously, and Remesh's OnDemand Recruit option supplies vetted participants when a team does not have its own panel ready. In Analyze, AI processes the responses and surfaces the ideas that the group collectively stands behind, so a researcher can see not just what was said but how widely a view was shared. Remy, an agentic AI layer, supports the research process itself. Three audiences are targeted most directly. Market research and consumer insights teams use Remesh to test concepts, messaging and campaign reactions before launch. HR and internal communications teams use the employee listening setup to hear from thousands of workers and identify which concerns have broad backing. Healthcare and life sciences researchers get a variant tuned to the compliance and speed demands of that sector. Named customers include Nestle, Yum Brands, Barclays, Mercer and NASCAR. Against conventional survey tools, Remesh trades breadth for depth: it captures the reasoning behind answers rather than just the answer. Against traditional qual agencies, it competes on turnaround, with the pitch of usable insight inside about an hour. The trade-off is that it is an enterprise sales product, not a self-serve tool, so small teams will find the fit and the commitment level heavier than the work requires.

How do you use Remesh?

  1. 1Book a walkthrough with the team
    Remesh is sold through demos rather than self-serve signup. Request a session to see the platform and discuss which use case (market research, employee listening or life sciences) fits your team.
    Remesh — Book a walkthrough with the team
  2. 2Review the platform overview
    Before the call, read through how the hybrid insights model works: live dialogue combined with asynchronous collection and AI analysis. It clarifies what a session actually looks like.
    Remesh — Review the platform overview
  3. 3Design your conversation
    Build the questions and response structure for your session. This stage decides the quality of everything downstream, so align it to the specific decision the research is meant to inform.
    Remesh — Design your conversation
  4. 4Recruit participants if needed
    If you do not have an audience ready, use OnDemand Recruit to bring in vetted participants. Otherwise invite your own customers or employees to the live or async session.
    Remesh — Recruit participants if needed
  5. 5Collect responses and analyze results
    Run the session and let AI process the responses into themes and consensus signals. Review the output to see which ideas drew broad support and where opinion split.

Pros and cons

Pros

  • Live sessions with hundreds of participants produce qualitative depth that surveys cannot matchAI
  • AI analysis highlights which ideas have broad group backing, not just what was mentionedAI
  • OnDemand Recruit supplies vetted participants for teams without a ready panelAI
  • Separate playbooks for market research, employee listening and life sciencesAI
  • Named enterprise customers (Nestle, Yum Brands, Barclays) suggest it holds up at large scaleAI

Cons

  • Pricing is not published and access runs through a sales demo request, so self-serve evaluation is impossibleAI
  • Live sessions still require scheduling and participant coordination, so it is heavier than firing off a surveyAI
  • Participant volume depends on having a panel or paying for recruited respondentsAI
  • The insight layer is only as strong as the conversation design put in front of itAI
  • Small teams and one-off studies will likely find the enterprise commitment disproportionateAI

How much does Remesh cost?

Support

A public support centre with tips and troubleshooting sits alongside the sales-led onboarding process; Remesh also publishes case studies and webinars that document how teams run sessions.

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Features

Covers the full research cycle: conversation design, live and asynchronous collection, OnDemand participant recruitment, AI-powered analysis that shows collective support for ideas, and Remy, the agentic AI layer for research. Dedicated configurations exist for market research, employee listening and healthcare and life sciences work, with live and video formats supported.

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Frequently asked questions about Remesh

  • How do you use Remesh?
    The walkthrough on this page covers 5 steps: 1. Book a walkthrough with the team 2. Review the platform overview 3. Design your conversation 4. Recruit participants if needed 5. Collect responses and analyze results.
  • What platforms does Remesh support?
    Remesh is available on Web App.
  • What are the limitations of Remesh?
    Pricing is not published and access runs through a sales demo request, so self-serve evaluation is impossible. Live sessions still require scheduling and participant coordination, so it is heavier than firing off a survey. Participant volume depends on having a panel or paying for recruited respondents.

Status

StatusActive
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Added10/22/2026

Platforms

Web App

Pricing

Paid