Emotix

Stop guessing. Validate your startup idea with proof

65 followers

Stop guessing. Validate your startup idea with proof

65 followers

Emotix finds real Reddit threads, App Store reviews, and competitor data to validate your startup idea in 5 minutes. Not AI-generated summaries. Actual links, quotes, and numbers from the live internet. So you build what people actually want.

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Launch tags:SaaS•Artificial Intelligence

Launch Team / Built With

getviktor.com — An AI coworker that actually does the work

An AI coworker that actually does the work

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EmotionSense Pro

Maker

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Hey PH! I'm Agshin, founder of Emotix. Built this in Estonia, originally from Azerbaijan. Here's why this exists. Last year I spent 3 months building a product nobody wanted. I did what every founder does. Asked ChatGPT "is this a good idea," got a beautiful 2000 word analysis that basically said "yes, go for it." It sounded smart. It was completely useless. The market had moved on 6 months before I even started. There were 4 competitors I never found. And the actual users I was targeting? They were on Reddit saying they solved the problem with a Google Sheet. I found all of this out AFTER I built. That moment when you realize you wasted months because an AI told you what you wanted to hear? That's what broke me enough to build Emotix. The problem with using ChatGPT for market validation is simple: it doesn't know what's happening right now. It gives you plausible sounding analysis based on training data. It sounds confident. It's often wrong. And you can't click any of its "sources" because they don't exist. Emotix is different because it goes and actually looks. You tell it your idea. It comes back with real Reddit threads where people are complaining about the exact problem you want to solve. With links. With dates. With actual quotes. It finds your competitors' App Store reviews and shows you what users hate about them. It estimates willingness to pay based on what similar tools charge and how people react to those prices. Then it gives you a validation score based on real signals, not vibes. It's opinionated too. It will tell you "this space is crowded, but here's a niche nobody is serving" or "literally nobody is searching for this, you should pivot." I wanted a tool that treats me like an honest cofounder, not a yes man. We have 261 early testers using it now. Some of them killed ideas that would have wasted their time. Some found niches they never would have spotted. Both of those are wins. What I'd love from you today: Try it with your current idea or a side project you've been thinking about. Tell me if the evidence it finds changes your mind about anything. And if it doesn't find good evidence, tell me that too. That feedback is gold. This is early. The product is rough in places. But the core thing, finding real evidence from the live internet instead of generating plausible fiction, that works. And I think it matters. Thanks for checking it out. Agshin

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1mo ago

Pulling actual Reddit threads and App Store reviews instead of summaries is a strong choice.
A lot of validation tools feel convincing until you try to trace where the insight came from.
How do you decide which signals are actually meaningful vs just loud opinions?

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1mo ago

EmotionSense Pro

Maker

@luca_ardito

Great question. We don't treat all signals equally.

The system scores by source type and recency. A Reddit thread where 50 people discuss a real pain point weighs more than one blog post with an opinion. G2 reviews from verified users weigh more than a random tweet.

We also filter hard. If a data point has no traceable source URL, it gets thrown out. No URL = no card. That was a deliberate decision because most AI tools sound confident while making things up.

The honest answer though: signal vs noise is still the hardest part. We recently added source diversity scoring, so if all your evidence comes from one website, the system flags that as weak. Still improving this every week.

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26d ago

The competitor data piece is the most interesting part to me. How does Emotix know which competitors are relevant to an idea it's never seen before? Is that user-defined, or does the system infer it? Because getting that mapping wrong would skew the whole validation.

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1mo ago

EmotionSense Pro

Maker

@sounak_bhattacharya

Both, actually.

When you describe your idea, AI agents first extract the core market and category. Then they run real searches across G2, Reddit, ProductHunt, Crunchbase, and industry reports to find companies operating in that space.

You can also name specific competitors directly, and the system will pull their pricing, reviews, features, and positioning from real sources.

The inferred mapping is where it gets tricky. You're right that getting it wrong skews everything. So we show you exactly which competitors were found and where the data came from. Every company card has clickable source URLs. If the system pulled the wrong competitor, you can see it immediately and redirect with a follow-up message.

No black box. That was the whole point of building it this way.

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26d ago

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