Decisions you can defend.
Vyrdis turns scattered user feedback into evidence-backed product decisions. Every recommendation traces back to the original quote.
No credit card. Export or delete your data anytime.
- Customer quote
- “I had to go find our VAT number before I could even see the product. Gave up and came back two days later — and then I had to start over anyway.”
- Fact
- Setup asked for billing details before anything else
- The user had to leave the product to find them
- Setup was abandoned at the first step
- Progress was not saved on return
- Hypothesis
- Users abandon onboarding because the first step asks for data they don't have yet.Evidence strength +7.4 on a scale from minus 10 to plus 10. Strongly supported by 14 facts.
- Recommendation
- Move company details to after the first successful action, and save progress between sessions.
Research keeps happening. Knowledge keeps disappearing.
The same insight, found twice
Last quarter someone interviewed users about onboarding. This quarter someone is doing it again. Nobody knew the work was already done.
Insights lost to the void
Notion docs nobody opens. Slack threads buried in three weeks of standups. Reports presented once, then forgotten.
Decisions you can't quite back up
Someone asks 'why this and not that?' — and the gap between your answer and the evidence is wider than you'd like.
Every recommendation traces back through every step that built it.
Feedback
Bring in everything users tell you — CSV imports, an embedded widget, API, manual entry. One place.
Facts
AI breaks each piece of feedback into concrete claims — problems, needs, observations. You review and approve.
Hypotheses
Facts cluster into hypotheses about what users actually want. Each one shows how strong the evidence is, on a scale from −10 to +10.
Recommendations
Recommend an action — and Vyrdis shows the chain back to every quote that supports it.
The AI does the heavy lifting. You keep the final say.
Vyrdis reads your feedback and proposes how each piece connects — which quote supports which hypothesis, and how strongly. You review every suggestion and approve, edit, or reject it. Each recommendation traces back to the original quote, so you can show your work when someone asks why. The AI saves you the manual reading; you keep the judgement.
“I had to go find our VAT number before I could even see the product.”
“I gave up at the first screen — I didn't have the company details on hand.”
support the same hypothesis
Users abandon onboarding because the first step asks for data they don't have yet.
Yesterday's strong evidence isn't always today's.
Hypotheses update themselves — as users change, and as your team actually fixes things.
Make a change based on a hypothesis, and watch what happens. If you actually solved the problem, complaints stop coming in and the score fades on its own. If it stays steady, you have a signal — not a guess — that something else is going on. Behind the score: every fact has a date, and newer ones count for more. A hypothesis without recent support gets weaker over time. New patterns in incoming feedback surface new hypotheses.
Strength score for one hypothesis. The decline after a fix is the signal it worked.
Built for product people who answer 'why'
UX designers and researchers
Stop redoing the same work. Build a knowledge base that gets more valuable the longer you use it.
Product managers
Defend prioritization with evidence, not gut feel. Show the chain when stakeholders ask.
CX and support leaders
Turn the feedback already flowing through your inbox into product decisions, without another tool to babysit.
Your data stays in Europe, and stays yours.
Vyrdis runs on European providers, end to end. That was an architecture decision, not just a compliance checkbox. And whatever you put in, you can take back out.
Hosted in Germany
Vyrdis runs on Hetzner Cloud in Nuremberg, a German company under GDPR and German data-protection law. Backups run daily.
Analysed in France
Mistral in Paris handles the AI analysis. Your customers' feedback is not used to train anyone's models — it stays yours.
European-owned
Vyrdis is made in Norway, with only European subprocessors. That puts it outside US extraterritorial data laws such as the CLOUD Act.
Yours to export or delete
Export everything to JSON or ZIP whenever you want. Delete your account, and everything tied to it goes with it. No support ticket required.
Built by someone who was drowning in it.
Vyrdis was founded by Jonas Lillevold and built on years of UX research practice. After watching feedback pile up across Notion docs, Slack threads, and reports nobody read, the question stopped being 'how do we collect more?' and became 'how do we make what we already have count?' Vyrdis is the answer to the second question.
Be among the teams shaping how Vyrdis works.
Vyrdis is in early access right now. The first teams in get to shape how it works — direct line to the founder, real input on what gets built next. It's free for the duration. Pricing arrives alongside the public launch later this year.
No credit card. Your beta org becomes your paid org when pricing rolls out — same data, same setup.
Stop relearning what you already knew.
Evidence that updates. AI you can audit. Free during early access.