The Short Answer
Listen Labs and Strella are both real AI-moderated interview platforms, but they are not really competing for the same buyer. Listen Labs is the scale play — $100M raised, a $500M valuation, over one million participants run through the platform, and a consumer-brand customer list. Strella is the depth play — $18M raised, a hybrid model that lets AI-moderated and human-led interviews live in the same project, and an enterprise per-study engagement.
Choose Listen Labs if you need large-sample consumer research with supplied panel and video, audio, and text modalities. Choose Strella if you want AI interviews that a human researcher can step into, on focused B2B or strategic studies. Choose neither if what you actually need is continuous research with your own customers — both are per-study enterprise engagements starting in the five figures, and neither offers a self-serve path.
Where Each Company Actually Stands
| Listen Labs | Strella | |
|---|---|---|
| Total raised | ~$100M | $18M |
| Latest round | $69M Series B (Ribbit Capital) | $14M Series A (Bessemer) |
| Valuation | $500M | Not disclosed |
| Founded | — | 2023, New York City |
| Founders | — | Lydia Hylton, Priya Krishnan |
| Named customers | Microsoft, Sweetgreen, Chubbies, KJT Group, Emeritus | Amazon, Duolingo, Apollo GraphQL, Chobani |
| Disclosed traction | 1M+ participants; 15x revenue growth in 9 months | $1.6M ARR, 150% net dollar retention (2025) |
| Typical entry price | ~$20K annual base + $300–400/session | ~$10K–$25K+ per study |
| Modalities | Video, audio, text | AI-moderated, mixable with human-led sessions |
Listen Labs' Series B was led by Ribbit Capital with participation from Evantic and returning investors Sequoia Capital and Conviction, following an earlier $27M round. Strella's $14M Series A was led by Bessemer Venture Partners, with Decibel, Bain Future Backed Ventures, MVP Ventures and 645 Ventures joining the seed investors from its original $4M round.
The funding gap is real, but it tells you less than the pricing model does.
The Real Difference: Panel Volume vs Human-in-the-Loop
Listen Labs is built around throughput. Its pitch is qualitative depth at survey scale, and the operational machinery reflects that — the annual base largely funds a recruitment operations team and methodology consulting, and the per-session fee covers participant incentives and the manual recruitment work behind them. Over a million participants have moved through the platform. If your research question is "what do 500 consumers think," this is the model built for it.
Strella is built around the hybrid. Its distinguishing feature is that AI-moderated and human-led interviews can run in the same system, on the same project. A researcher can let the AI handle the first 30 conversations and personally moderate the five that matter most, with everything synthesized together. Founder Lydia Hylton frames the original problem plainly: getting to 30, 40, or 50 interviews on a topic was traditionally too painful with human-led sessions, so teams defaulted to surveys and lost the depth.
Strella also reports a finding worth taking seriously across the whole category: participants appear more honest with AI moderators than with humans. That is the strongest argument for AI moderation that exists, and it is not a throughput argument — it is a data quality one. We dig into the evidence in are AI-moderated interviews reliable?
Where Both Models Get Expensive
The pricing structures diverge, but both land in the same place: a five-figure commitment before your first insight.
Listen Labs quotes roughly a $20K annual base plus $300–400 per session, with custom services scoped on top. A 40-participant study is therefore $12,000–$16,000 in session costs on top of the base — so year one on a modest research cadence realistically starts around $35K–$50K.
Strella uses an enterprise per-study model at roughly $10K–$25K+ per engagement, with seat-based components. Its 150% net dollar retention says customers expand once they are in, which is a genuine signal of value — and also a signal that the entry price is not the steady-state price.
Neither number is unreasonable for what enterprise qualitative research used to cost. A traditional agency study runs comparable money and takes six weeks. But both models share a structural constraint: research becomes an event you budget for, not a habit you build. When each study costs five figures, teams run four a year and route every question through a committee. Our user research tool pricing breakdown puts these numbers in context against the legacy platforms.
There is also the procurement tax. Neither platform has a self-serve tier, which means the full approval gauntlet — security review at a median of 28 days, legal redlines at 2–8 weeks, procurement approval at 2–6 weeks — happens before you run a single interview. See how to get a research tool through procurement.
Which One Should You Pick?
Pick Listen Labs if: you run consumer research at scale, you need participants supplied rather than sourced from your own base, you want video and audio alongside text, and you have a research budget that treats $40K+ as normal. The enterprise brand list and the participant volume are genuine.
Pick Strella if: your research is B2B or strategic, sample sizes are smaller but stakes are higher, and you want a human researcher able to take the wheel on the interviews that matter. The hybrid model is the most thoughtful answer in the category to the objection that AI moderation cannot handle nuance.
Pick neither if: the people you most need to talk to are already your customers. This is the gap both platforms share. Their economics are built around sourcing strangers who match a profile — which is the right model for concept testing and market sizing, and the wrong model for understanding why your own users churned, what your trial abandoners hit, or how your buying committee actually decided.
The Third Option: Your Own Customers, Continuously
Koji is built for the research question that starts with "our customers." Instead of paying $300–400 to recruit a stranger who matches your ICP, you interview the people already in your CRM, your trial list, or your churn export.
AI-moderated voice and text interviews probe follow-ups automatically — when an answer is shallow, contradicts something earlier, or carries an emotional cue, the AI digs, exactly as a good researcher would. There is no human moderator in the room, so no moderator bias shapes the answers. Thematic analysis runs automatically across every transcript, with each theme traceable back to the verbatim quotes behind it, and one-click reports are ready in hours rather than weeks.
Unlike either platform here, a Koji study is not purely open conversation. Six structured question types — open_ended, scale, single_choice, multiple_choice, ranking, and yes_no — sit inside the same AI-moderated session, so one study produces both the quotable narrative and the chartable distribution. You do not run a survey and interviews separately and then try to reconcile them.
The commercial model is the sharpest contrast:
- Insights: €29/month (29 credits). Interviews: €79/month (79 credits). Enterprise available for larger deployments.
- Credits are consumed at 1 per text interview, 3 per voice interview, 5 per report refresh — overage is a flat €1/credit.
- A quality gate means only conversations scoring 3 or higher consume a credit. Abandoned and junk sessions do not bill you, which is not true when you are paying $300–400 per recruited session regardless of what it yields.
- Self-serve. No annual base, no per-study scoping call, no procurement cycle before your first interview.
On data, Koji is EU-built and EU-operated: compute on Vercel in Paris (cdg1), database and uploads on Supabase in Paris (eu-west-3), a DPA available to every business customer rather than gated to an enterprise tier, and a publicly published sub-processor list. For teams evaluating AI research tools against 2026 obligations, the EU AI Act and user research and our AI interview data privacy guide cover what to verify.
The Honest Summary
Listen Labs and Strella are both good products solving a real problem, and if you need supplied panel at consumer scale, Listen Labs' machinery is hard to replicate cheaply. But both price research as a project. The teams getting the most out of AI research in 2026 are not running four expensive studies a year — they are asking their own customers something every week, because the marginal cost of asking is close to zero.
Try Koji for €29/month — bring your own customers, run an AI-moderated voice or text study this week, and get a themed report with traceable quotes in hours. No annual base, no per-session recruitment fee, no procurement cycle.
Comparing more of the field? See Koji vs Listen Labs, Koji vs Strella, and the full buyer's guide to AI customer interview tools.
