✓ The framework got all 10 right. Byju's flagged RED before its 95% collapse. Nykaa GREEN before profitable IPO. CRED RED despite top-tier backers. Score your own deal →
★ Open ledger · updated 2026-05-01

10 famous Indian startups, scored at their peak. The framework got all 10 right.

AK
Scored by
Amish Kapadia · 28 years on Wall Street (Citibank → FHLB Boston → Sanwa → JP Morgan → Barclays → Nomura). Active angel investor in India since moving back to Mumbai in 2023. No sponsor, no fund affiliation, no paid placements. More about me →

If you're an angel writing your first cheque, an NRI eyeing an Indian deal, or a founder trying to read your own numbers — you need a way to spot bad deals from good ones, without depending on hype or famous backers.

So I built one. Then tested it. Picked 10 famous Indian startups. Scored each at a historical inflection point (peak hype, pre-IPO, or latest round). Recorded the verdict — 🔴 RED, 🟡 AMBER, or 🟢 GREEN. Then waited to see what actually happened.

⚡ Score your own deal — free, 8 minutes → See what we found ↓
What the bands mean

3 verdicts. Plain English.

🟢
GREEN — Numbers check out
Worth a deeper conversation. Score 70+ on the framework. Doesn't guarantee a winner — but the deal clears the bar on the data we can see. Run reference calls and proceed.
🟡
AMBER — Real gaps
Score 45–69. Don't write a cheque without specific answers on what's missing — usually unit economics, founder equity, or stretched valuation. Possible recovery, but not on the inputs alone.
🔴
RED — Walk away
Score below 45. The framework caught structural problems that won't fix with more time or capital — bad unit economics, stacked warning signals, valuation disconnected from numbers. Pass.
What we found

10 startups scored. 10 outcomes verified.

Every prediction below was scored using only data available at the snapshot point. If a startup peaked in 2021, I used 2021 numbers — no hindsight. The full reasoning, source data, and outcome verification is on each card. See the framework methodology →

Total scored
—
GREEN band
—
AMBER band
—
RED band
—
Framework validation — predictions matching outcomes
—
Calculation: scorecards where the predicted band matches the realised outcome (e.g., RED prediction + later collapse = match).
Filter: Sector:
Methodology

How we score — 100 points across 8 weighted dimensions

Each scorecard runs the same algorithm. Score is weighted by stage (early-stage rewards growth + traction; late-stage rewards capital efficiency + valuation discipline). Bands: GREEN ≥70 · AMBER 45–69 · RED <45. Manual override allowed when 3+ warnings stack (see Paytm at 74 → AMBER call).

Runway · 20 pts × stage
Cash ÷ net burn. ≥18m = full · 12-18m = 14 · 6-12m = 8 · <6m = 0 + warning.
Unit economics · 25 pts × stage
LTV/CAC ≥3x = full · 1.5-3x = 12 · <1.5x = 0 + warning. Plus payback period bonus.
Growth + margins · 25 pts × stage
MoM growth: ≥20% strong, ≥10% decent. Gross margin: ≥60% healthy, 30-60% watch, <30% weak.
Cap table · 8 pts
Founder equity ≥50% aligned · 30-50% diluted · <30% needs explanation. Plus DPIIT + investor pedigree.
Valuation · 8 pts × stage
Revenue multiple vs stage-aware ceiling. Sector benchmarks (consumer ~12x, fintech ~25x, SaaS ~30x) used for sanity.
Capital efficiency · 5 pts
Annual revenue ÷ total raised. ≥0.5x healthy · 0.2-0.5x fair · <0.2x burning vs earning.
Round trajectory · ±5 pts
Up-round momentum +5 · Flat round neutral · Down-round −5 + warning. Months-since-last-raise factored in.
DD completeness · 15 pts × stage
10-question qualitative checklist (founder track record, customer references, legal cleanness, etc.). Weighted by stage.
Framework v1.0 — known limitations
  1. Stack-penalty gap: Doesn't compound when 3+ warnings co-occur. Paytm at 74 should arguably be RED, not AMBER. v1.1 will add a stack multiplier.
  2. Brand-pedigree weight: Reputable lead investor adds +5. CRED at 36 RED was barely caught despite Tiger / GIC / Sequoia. Capping the +5 to +3 when other warnings stack is on the v1.1 list.
  3. Anti-pattern detection works: Zerodha (counterfactual, never raised) scores 86 GREEN — the framework rewards underlying business strength, not raise narrative. Confirmed by validation set.

Data quality: Public filings (DRHPs, MCA), founder interviews, news reports, secondary-market trades. Each scorecard tags its data source. Honest disclosure: these are point-in-time snapshots — markets move, and the framework is not a substitute for legal/financial DD before committing capital. Run the same algorithm on your own deal →

Score your own startup with the same framework

The free Startup Scorecard tool runs the same 8-minute screening on any deal — for founders self-screening pre-pitch, or angels evaluating before a meeting.

Run the Scorecard →