Base Revenue = 100
DCF Valuation Summary
EV/NTM Multiple Breakdown
Year-by-Year Projections
| Year |
Revenue |
FCF |
Discount Factor |
PV (Pre-Dilution) |
Dilution Factor |
PV (Post-Dilution) |
Sensitivity Analysis: EV/NTM Multiple (WACC x Terminal Growth)
Sensitivity Analysis: EV/NTM Multiple (CAGR x FCF Margin)
| CAGR / FCF |
15% |
20% |
25% |
30% |
35% |
40% |
Sensitivity Analysis: EV/NTM Multiple (SBC Dilution x WACC)
| SBC / WACC |
8% |
9% |
10% |
11% |
12% |
DCF Valuation Results
Terminal Contribution
-
-
DCF Terminal Multiple
-
At Year 10
Market Implied Terminal
-
Multiple at Year 10
Implied Terminal Growth
-
Gordon Growth Rate
Terminal Growth Comparison
-
-
EV/NTM Multiple Breakdown
Year-by-Year Projections ($M)
| Year |
Revenue |
FCF |
Discount Factor |
PV (Pre-Dilution) |
Dilution Factor |
PV (Post-Dilution) |
DCF Sensitivity Analysis (Implied Upside/Downside %)
10-Year CAGR vs FCF Margin
10-Year CAGR vs Terminal Growth
Default Assumptions (Company-Specific)
10-Year CAGR
NTM Growth × 70%
FCF Margin
>30%: actual
10-30%: 30%
0-10%: 15%
<0%: 10%
SBC Dilution (Implied)
>3%: 3%
2-3%: 2%
1-2%: 1%
<1%: actual
SBC% ÷ EV/S
WACC (by NTM Rev)
>$10B: 9%
$5-10B: 10%
$2-5B: 11%
<$2B: 12%
Terminal Growth
>30% NTM: 5%
20-30%: 4%
10-20%: 3%
<10%: 2%
DCF Valuation Ranking (Sorted by Upside)
| Company |
Description |
Current EV |
NTM Rev |
NTM Growth |
10Y CAGR |
LTM FCF |
FCF Used |
SBC Used |
WACC |
Term. Growth |
DCF Value |
Upside |
Current EV/S |
DCF EV/S |
Mkt Term. Growth |
SaaS Comps Table (Click headers to sort)
| Company |
Description |
Mkt Cap ($M) |
EV ($M) |
NTM Rev ($M) |
NTM Growth |
NTM EV/Sales |
LTM Rev ($M) |
LTM Growth |
LTM OPM % |
LTM FCF % |
LTM OpEx % |
LTM SBC % |
Short Ideas Deep Dive
At-risk or transitioning companies (GenAI Score <70) still trading at premium to DCF value. Potential structural headwinds from AI disruption.
Long Ideas Deep Dive
Well-positioned companies (GenAI Score 70+) with DCF upside or minimal downside. Beneficiaries of AI transition.
SaaS GenAI Positioning Rubric v2.0 (100 Points)
Score each company on 10 factors. Each factor is worth 10 points. Total = 100.
Dimension 1: Business Model Resilience (20 pts)
1. Pricing Model Alignment (10 pts)
Does the pricing model align with AI value creation?
| 10 | Pure consumption/outcome-based; AI usage = more revenue (SNOW, DDOG) |
| 7 | Hybrid: seat + meaningful usage component |
| 4 | Seat-based with AI add-on SKU |
| 2 | Pure seat-based; AI productivity threatens revenue |
2. AI TAM Impact (10 pts)
Does GenAI/AI expand, maintain, or shrink the company's total addressable market?
| 10 | TAM expands significantly: AI creates new use cases, unlocks new segments, increases WTP |
| 7 | TAM grows modestly: AI adds adjacent capabilities or new buyer personas |
| 4 | TAM flat: AI neither helps nor hurts the addressable market |
| 2 | TAM shrinks: AI commoditizes the space or eliminates need for the product |
Dimension 2: Competitive Moat vs. AI Natives (30 pts)
3. Data Moat & Gravity (10 pts)
Does the company possess proprietary data that gets MORE valuable in an AI world?
| 10 | Data gravity: customers consolidate data; AI needs this data (SNOW, PLTR) |
| 7 | Valuable proprietary data that improves AI capabilities |
| 4 | Data is useful but portable; AI natives can acquire |
| 2 | Data becomes LESS necessary; easily synthesized |
4. Write Path / Execution Depth (10 pts)
Is the product in the "write path" (executing decisions) or "read path"?
| 10 | Deep write path: executes mission-critical transactions (payment rails, ERP) |
| 7 | Moderate: captures decisions; agents need this data to act |
| 4 | Mixed: some execution but mostly read-path |
| 2 | Pure read path: receives data after decisions; easily bypassed |
5. Regulatory/Compliance Barrier (10 pts)
| 10 | Heavy regulatory moat: licenses, certifications, audits (fintech, healthcare) |
| 7 | Industry-specific compliance: SOC2, HIPAA |
| 4 | Standard enterprise security only |
| 2 | No meaningful regulatory barrier |
Dimension 3: AI Disruption Vulnerability (30 pts)
6. Prompt-Away Risk — Near Term (10 pts)
Can core functionality be replicated by prompting an LLM TODAY or within 3-6 months?
| 10 | Cannot be prompted away: requires proprietary data, physical-world integration, regulatory infra |
| 7 | Very unlikely today: deep workflow complexity, domain expertise, multi-system orchestration |
| 4 | Partially today: some core features replicable but integration/data layer protects |
| 2 | Mostly today: LLMs can already replicate 80%+ of core value with basic tool use |
7. Subsumption Window (10 pts)
For software that can't be prompted away today — how many years until AI catches up?
| 10 | 5+ year runway: physical-world integration, regulatory complexity, proprietary infrastructure |
| 7 | 3-5 year runway: complex domain knowledge, multi-system orchestration, deep vertical expertise |
| 4 | 1-3 year runway: semi-structured tasks, patterns AI is rapidly learning |
| 2 | <1 year runway: AI capability frontier is closing fast on core functionality |
8. Vertical vs. Horizontal Positioning (10 pts)
Horizontal SaaS -49% since 2021; Vertical SaaS flat.
| 10 | Deep vertical: industry-specific workflows, compliance (healthcare, fintech) |
| 7 | Vertical-leaning: serves specific industries |
| 4 | Horizontal with vertical editions |
| 2 | Pure horizontal: generic productivity; competing with AI assistants |
Dimension 4: Structural Position & Health (20 pts)
9. Infrastructure vs. Application Layer (10 pts)
Where does the company sit in the AI value chain?
| 10 | Infrastructure: AI agents NEED this to function (databases, observability) |
| 7 | Platform hybrid: data + apps; foundation for AI workflows |
| 4 | Application with system-of-record status |
| 2 | Pure point solution: agent could fully replace |
10. Net Revenue Retention (10 pts)
NRR is the real-time indicator of customer value realization.
| 10 | >130% NRR — customers dramatically expanding |
| 8 | 120-130% NRR — healthy expansion |
| 6 | 110-120% NRR — solid but watch for deceleration |
| 4 | 100-110% NRR — flat; potential early churn |
| 2 | <100% NRR — contracting; disruption underway |
Score Interpretation
| Score | Tier | Investment Stance |
|---|
| 85-100 | AI Infrastructure / Clear Winner | Strong conviction; benefits regardless of AI outcome |
| 70-84 | Well-Positioned for AI Transition | Long with confidence; manageable transition risk |
| 55-69 | Uncertain / Transitioning | Selective; execution on AI strategy is critical |
| 40-54 | At Risk of Disruption | Underweight; structural headwinds evident |
| <40 | High Disruption Risk | Avoid; "prompt away" and seat compression risks material |
GenAI Positioning Ranking
Click any score cell to edit. Totals recalculate automatically. Click headers to sort.
| Company |
EV ($B) |
DCF ($B) |
Upside |
Score |
Tier |
Price |
TAM |
Data |
Write |
Reg |
Prompt |
Subsum |
Vert |
Infra |
NRR |
Rationale |