What is research AI?
At Lyssna, research AI is the use of artificial intelligence to support user research at every stage – not a single bolt-on feature. That includes:
Reach the right participants, and trust every response. AI recommends your filters and flags low-quality or fraudulent activity.
Get deeper, ready-to-read answers as your study runs. AI asks follow-up questions and summarizes results in real time.
Turn recordings into transcripts in minutes, and query your research from Claude or ChatGPT.
The difference research AI makes
Not just automation for its own sake – a real shift in how your team works.
Faster time to insight
Use research AI to help synthesize your results and generate insights faster.
Research anyone can run
Anyone on the team can run a study and understand the results.
Confidence you can defend
Every summary is grounded in real participant answers, so stakeholders trust what you bring them.
AI that earns your trust
Every AI feature is built to make a specific part of research faster, not to replace your judgment.
We never train AI models on your data, or your participants' data.
AI drafts summaries and flags patterns, you make the call on what they mean.
Human-in-the loop, so you're always in control.
Secure and compliant
Security that scales with you, from startup to enterprise.
We encrypt your data at all times.
We run regular security checks and vulnerability testing.
We're GDPR and SOC 2 compliant.
Trusted by industry leaders
From startups to global enterprises, leading teams rely on Lyssna to validate ideas, run studies, and make product decisions.
Get more from research AI
Resources for using AI throughout your research process.
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AI UX research
AI UX research can turn weeks of analysis into hours, but not every task is ready to hand over. See where AI helps in 2026, and where judgment still wins.
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MCP for AI research
The Model Context Protocol (MCP) lets AI assistants answer questions using your real research data. Here's what MCP is and how to use it for user research.
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AI UX design
AI UX design can speed up research, prototyping, and testing, but not every task benefits equally. See where AI helps UX teams, and where it still falls short.
