Snap a picture of your meal. Calzy's AI calculates calories, protein, carbs, fat — and tells you if what you're eating is actually good for you.
What this SaaS is
Calzy uses AI to analyze meal photos and provide nutritional information.
- AI meal analysis
- Nutritional breakdown
- User-friendly interface
- No active customers— Zero customers reported. Hard to model retention or growth.
- Founded <12mo ago— Less than 12 months of operating history. Retention is unproven.
- Stale / unmaintained site— Footer copyright is years old or blog hasn't been touched. Maintenance level is low.
Numbers that matter
Tech stack
Marketing channels
Score breakdown
How the composite score above splits across seven independent signals. Each axis is graded 0-100. Hover for details.
Payback period, asking price vs category median multiple, and 30-day profit margin.
30-day MRR delta, with a small bonus when historical snapshots confirm a sustained climb.
Revenue per visitor, customer count, plus live-site UX signals (pricing reachability, core pages, copyright freshness).
AI-disruption risk, presence on review platforms (G2, ProductHunt, AppSumo…), penalty when built on no-code rails.
Diversity of marketing channels, Merchant-of-Record status, cofounder count. Solo founders and no-code stacks get docked.
Listing freshness, payment provider trust, business age, customer concentration. Higher score = less risky.
Structured market read across TAM, saturation, 3-year trend, and hype cycle, blended with our category momentum signal.
Market read
- TAMmid
The app targets a broad consumer base, indicating a mid-sized market.
- Saturationmature
The market for health and fitness apps is well-established and competitive.
- 3y trendgrowing
Consumer interest in health tracking has increased, driving growth.
- AI disruptionwrapper killable
The core functionality can be replicated easily by solo developers.
- Hype cyclemainstream
Health apps are widely adopted, placing them in the mainstream phase.
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