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// PLATFORM

Risk MatchingMethodology

// COMPANY

AboutPricingContact

// EXPLORE

AutopsiesRankingsInvestors

In 86% of analyses, the collapse pattern is already in our database (72% exact primary cause).

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© 2026 UnicornBurn
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// PRODUCT

Six tools.
One workflow.

The only risk workflow built on 4,998 verified startup autopsies. From structural match to IC-ready memo — in one platform, without manual work.

Start free →See pricing
4,998 verified autopsies86% Top-3 accuracy15 structural dimensions6 native integrations
  1. 01Describe the startup→
  2. 02Get Risk Score→
  3. 03Read survival curves→
  4. 04Generate IC memo→
  5. 05Monitor portfolio
// 01Risk Match Engine

Cross-reference any company against every documented collapse.

A startup is matched against 4,998+ verified autopsies across 15 structural dimensions: sector, country, funding stage, moat type and strength, hype cycle position, business model, B2B/B2C, founding year, archetype, primary fatal mistake, and more. A Naive Bayes + retrieval ensemble predicts the most likely failure causes — 86% Top-3 accuracy (72% exact primary cause), validated on n=3,421. No black box — every score is traceable to specific signals.

→ VC associates · Deal teams · Pre-IC review
Run a risk match →
// match result
RISK SCORE
87 / 100 · HIGH

CAUSE DISTRIBUTION
Unit Economics (34%)
Premature Scaling (28%)
Competition (19%)

TOP MATCH
WeWork — 92% structural similarity
SaaS · $47B peak · office-sharing moat
Collapsed 14mo after S-1 withdrawal

CAUSE PREDICTION (NB + ENSEMBLE)
Unit Economics 34% ← primary
Premature Scaling 28%
Competition 19%
Accuracy: 86% Top-3 · 72% primary · n=3,421
// 02Survival Probability

Historical survival rates for your exact structural profile.

Kaplan-Meier survival curves built from real collapse sequences — not industry averages or analyst opinion. For your matched cohort, you get survival probability at 12, 24, and 36 months. Rates are stratified by dominant cause, so you can see whether the risk peaks early (PMF failure) or late (unit economics/scaling).

→ GPs · Partners · Investment Committees
How we compute the curves →
// survival curve · SaaS B2B · Series B · EU
COHORT
847 comparable collapses
Median survival: 28 months

SURVIVAL RATE
12mo 24mo 36mo
All causes 68% 44% 31%
Unit economics 61% 38% 24% ← dominant
Premature scale 71% 49% 35%
Competition 74% 52% 41%

INTERPRETATION
Unit economics dominant → 24mo survival: 38%
Cohort average: 44%
// 03IC Memo GeneratorHIGHEST ROI

From risk match to IC-ready memo. In minutes.

Three output formats generated from your match results — each targeting a different audience. IC Memo: full risk analysis with score rationale, cause breakdown, survival interpretation, top 3 comparable collapses, DD questions, and LP-ready language. IC 1-pager: condensed executive summary for committee review. LP Note: investor-facing narrative framing the risk in portfolio context. The 3–4 hours your analyst spends building this, automated — without sacrificing analytical rigour.

→ Analysts · Associates · Deal teams
Try the IC memo generator →
// IC memo · excerpt
RISK ASSESSMENT MEMO
Target: [Company] · Series B · B2B SaaS · Spain
RISK SCORE: 87/100 · CLASSIFICATION: HIGH

EXECUTIVE SUMMARY
Structural profile matches 847 documented collapses.
Dominant pattern: unit economics failure, Series B, EU.

PRIMARY RISKS
1. Unit Economics (34%) — CAC payback signals danger zone
2. Premature Scaling (28%) — headcount / ARR ratio elevated

DUE DILIGENCE TRIGGERS
□ Request 24-month cohort LTV/CAC by channel
□ Benchmark CAC payback vs. sector median (18mo)

OUTPUT FORMATS
→ IC Memo (full · PDF)
→ IC 1-pager (executive summary)
→ LP Note (investor narrative)
// 04Portfolio Monitor & Alerts

Know when a startup's risk profile shifts — before it's a problem.

Weekly or daily structural risk alerts across your full portfolio. When a company matches new historical patterns — shifted hype cycle position, new funding stage, changed business model — you get notified with the updated risk score and the specific signals that triggered the change. Only structural shifts that move the score by a meaningful threshold.

→ Fund managers · GPs · Family Offices
Set up portfolio monitoring →
// weekly portfolio digest
PORTFOLIO RISK DIGEST · Week of 2026-06-09

RISK CHANGES (2 companies)
⚠ Company A · Risk Score 71 → 84 (+13)
Trigger: hype cycle shifted to POST_PEAK
New dominant cause: Competition (was Unit Economics)
Recommended: review competitive moat assumptions

✓ Company B · Risk Score 62 → 57 (−5)
Trigger: Series B closed — funding stage updated
Survival 24mo: 49% → 54% · No action required

STABLE (7 companies) · No significant changes
// 05Native Integrations

Risk analysis in your existing workflow — not a new tab.

Sync risk analysis results directly into your Notion deal rooms, Airtable portfolio trackers, Affinity CRM, Visible reports, Excel workbooks, or Google Sheets. Risk scores, cause distributions, and comparable collapses appear as structured fields — no copy-paste, no reformatting. Your existing workflow gains risk intelligence without adding tool overhead.

→ All investment team roles · Enterprise
Connect your tools →
// sync to Notion deal room
UNICORNBURN → NOTION SYNC
Deal: Series B — [Company Name]
Last synced: 2026-06-09 09:14

SYNCED FIELDS
Risk Score 87 / 100
Risk Classification HIGH
Dominant Cause Unit Economics (34%)
Comparable Cases WeWork · Homejoy · Fab.com
Survival 24mo 44% (cohort avg)
IC Memo [attached PDF]

STATUS ✓ Synced to /deals/series-b/[company]/risk
// 06Full API Access

Programmatic access to 4,998+ documented autopsies.

Filter, query, and export the full autopsy dataset. Filter by collapse style, hype cycle phase, moat type, geography, funding stage, business model, and timeline events. Build risk intelligence into your own models, fund management platforms, or research pipelines. Rate limits scale with your plan; full dataset available on Fund tier.

→ Quant funds · Tech-forward PE · In-house platforms
View API docs →
// GET /api/autopsies
GET /api/autopsies
?sector=Fintech
&collapseStyle=Regulatory+Kill
&country=spain&limit=3

HTTP 200 OK · 47 results

[{
"name": "Aplazame",
"sector": "Fintech",
"country": "Spain",
"causeCategory": "Regulatory Kill",
"totalFundingM": 12,
"survivalMonths": 34,
"timeline": [...]
}]

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