Startup Scorecard
A

SupplyChain AI

Predictive intelligence for global supply chains

SaaSSeries B$100M - $500M
Final Score
84
Tier 2: High Growth / Low Moat

Negotiate valuation

Investment Decision

Tier 2: High Growth / Low Moat

Likely burn-heavy with stiff competition

Recommended Action

Negotiate valuation

Headquarters

Chicago, IL

Founded

2019

Employees

180-220

About

SupplyChain AI uses machine learning to predict disruptions and optimize global supply chains. Our platform has saved customers over $500M in avoided disruptions and inventory costs.

Weighted Scoring Breakdown
Execution Power

Weight: 30%

80.0

Founder-Market Fit + Revenue Velocity

Capital Efficiency

Weight: 30%

87.5

Burn Multiple + LTV/CAC

Durable Moat

Weight: 25%

90.0

Proprietary Data + Integration Depth

Growth Potential

Weight: 15%

77.5

NRR + K-Factor

Evaluation Metrics (1-100 Scale)
Founder-Market FitTarget: 10+ yrs domain + serial exit

15 yrs domain exp + serial exit

Revenue VelocityTarget: >200% YoY Growth

95% YoY ARR Growth

Burn MultipleTarget: <1.0x

1.20x (Net Burn / Net New ARR)

LTV/CAC RatioTarget: >5x

8.0x ($280K / $35.0K)

Proprietary DataTarget: >80%

82% private data

Integration DepthTarget: >5 active hooks

11.5 avg APIs per user

Net Revenue RetentionTarget: >120%

140% NRR

K-FactorTarget: >1.0

0.54 (1.5 invites x 36% conv)

Key Employees
WC

William Chen

CEO & Co-Founder

Former SAP, supply chain VP

DLW

Dr. Lisa Wang

CTO & Co-Founder

Stanford ML, operations research PhD

RM

Robert Martinez

Chief Revenue Officer

Former Oracle, $200M quota carrier

Financial Metrics

Revenue (ARR)

$32M ARR

+95% YoY

Gross Margin

79%

Burn Rate

$1.5M/month

Runway

28 months

LTV

$280,000

CAC

$35,000

Investment Details
Total Raised$92M
Last Round$60M Series B
Last Round DateJune 2024
Target Raise$120M Series C
Minimum Investment$300,000

Lead Investors

Insight PartnersSapphire Ventures
Key Highlights
  • $500M+ saved for customers in disruption avoidance
  • Predicts disruptions 3 weeks in advance with 92% accuracy
  • 150+ enterprise customers including 20 Fortune 500
  • Real-time visibility across 10,000+ supplier networks
Risk Factors
  • Data quality dependency on customer systems
  • Long implementation cycles
  • Competition from ERP vendors adding AI features