Oleg IvanovThis is the second layer of Fluenta's pipeline. Layer one (scouting) surfaces what the market is talking about. Layer two — verification — cross-checks each idea against 25 live data integrations before assigning a Launch Readiness Score.
Why verification is separate from scouting
Scouting tells you something might be interesting. Verification tells you whether it actually is. A VC tweet is not a market. A headline is not demand. An accelerator cohort is not revenue.
To go from "plausible" to "backed by data," you have to hit the sources where real human behavior lives — and that's what verification does.
The six signal dimensions
Every idea is scored across the same six dimensions. Each dimension draws from multiple integrations so no single source can skew the result.
1. Demand — are people actively searching?
Integrations: Google Trends, related search data, autocomplete patterns, emerging AI-search signals. What we look for: sustained search volume, positive slope, and non-zero volume on long-tail variants.
2. Pain — are they complaining?
Integrations: Reddit, X, Quora, Substack, YouTube comments, community forums. What we look for: repeated complaints, not one-off vents. Complaints that cluster around the same workflow beat scattered rants.
3. Competition — can a new entrant win?
Integrations: Crunchbase, Product Hunt, web search, app stores. What we look for: how crowded the space is, how recently incumbents launched, and whether there's a positioning gap a smaller player can occupy.
4. Monetization — are people already paying?
Integrations: Product Hunt pricing, AppSumo, Acquire.com, Upwork, Fiverr, job boards. What we look for: comparable products with disclosed pricing, freelance spend on adjacent problems, and willingness-to-pay signals.
5. Funding — is capital flowing?
Integrations: Crunchbase, public funding databases, VC firm announcements. What we look for: money moving into the category over the last 6–12 months, not just one blockbuster round.
6. Urgency — are there triggers?
Integrations: regulatory news, tech-release feeds, narrative and trend trackers. What we look for: a reason this idea should launch now rather than next year — new regulation, new API, new platform, new crisis.
How the score is computed
Each dimension produces a sub-score. The sub-scores roll up into the Launch Readiness Score (LRS, 0–100). The weighting isn't uniform — dimensions with stronger predictive power in historical backtests carry more weight.
Crucially, the LRS is not static. Fluenta runs weekly backtests comparing past LRS predictions against what actually happened in the market, and re-tunes weights based on prediction accuracy.
Why 25 integrations and not 200?
Scouting (layer 1) casts a wide net — 200+ sources — because you want as many candidate ideas as possible.
Verification (layer 2) is narrower on purpose. Each integration has to deliver verifiable, structured, quantitative data in near-real-time. That's 25 sources today, and we add more as they prove their reliability in backtests.
What you see in the report
Every Idea X-Ray report shows:
- Sub-scores for all six dimensions
- The raw evidence that drove each sub-score
- Which integrations contributed
- The final LRS with its launch band
- An explicit recommendation
What this means for you
Without verification, you're guessing. "AI for pet grooming" sounds interesting until you learn the market is 12 people, 3 funded competitors, and zero search volume. Verification catches this in 20 minutes — before you spend 3 months building. The founders who use Fluenta's verification layer replace gut instinct with traceable evidence. Every number links back to a real source. You can challenge any score by clicking through to the raw data. That's not something you get from a brainstorming session with ChatGPT.
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