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AI that clusters, quantifies and explains qualitative feedback, with cited answers, spike alerts and churn impact. GDPR-first, EU-hosted. Free while in open beta.

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Website, pricing, platforms and company facts side by side.
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| Website | sentriment.com | diffee.me |
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| Company | Startup from Italy · 1 - 9 employees | — |
| Listed in |
In their own words, as submitted to SaaSHub.


Most feedback tools count votes on a public board. Sentriment reads everything instead, including the feedback nobody ever posts: support conversations, app store reviews, in-app messages, survey responses and imported spreadsheets. Every item is analyzed for sentiment, emotion, type and the...
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What each product offers, as listed by its team.


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How often each product is chosen within a category, 0–100% relative to the other.


As answered by people managing Sentriment and Diffee.
Sentriment's answer
TypeScript, Next.js, PostgreSQL, AI.
Sentriment's answer
Deep feedback analysis usually means an annual contract and a sales demo. Sentriment has a free plan, paid plans from €49/month with unlimited seats, and ranks themes by revenue, not volume. It's hosted in Frankfurt.
Sentriment's answer
Sentriment is the only that prices feedback in revenue. Groups feedback from your app, inbox and app-store reviews into themes, shows the MRR behind each one, and alerts you when a paying customer turns at-risk. Personal data is redacted before storage.
Sentriment's answer
Founders and product managers at early-stage B2B software companies with no analyst, who need to know what to build next and who's about to churn.
Sentriment's answer
Small teams collect lots of feedback but have no time to read it, and the tools that analyse it properly are priced for enterprises. We built Sentriment in 2026 to give small teams the answer: which problems matter, and what they cost.
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External articles and on-site reviews we used to compare the two products.


Having all the feedbacks in one central place with user profiles and money behind each really makes sense to me. I know what users are saying at scale with a money bias, which I think is the right approach. In...
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