Startup Valuation Engine

A Comprehensive Guide to Valuing Fast-Growing Pre-Revenue Companies

Theory, Methods, Regulation, and Practice — Valuation in Practice Series by Ascent Partners

Buy on Amazon View on GitHub

80+

Valuation Formulas

14

Python Modules

101

Unit Tests

60+

MCP Tools

Quick Start

pip install startup-valuation

from startup_valuation.core import scorecard_valuation
from startup_valuation.types import Scenario

result = scorecard_valuation(
    average_valuation=1_500_000,
    weights=[0.30, 0.25, 0.15, 0.10, 0.10, 0.05, 0.05],
    scores=[1.25, 1.50, 1.20, 0.75, 1.00, 0.90, 1.00],
)
print(f"Scorecard: ${result.value:,.0f}")  # $1,800,000

📚

Python Library

14 modules, 80+ typed functions, all returning ValuationResult with value, assumptions, and sensitivity analysis.

Explore API Reference →

🤖

MCP Server

60+ tools for AI agents (Claude, OpenCode, etc.) via stdio/SSE. Connect any MCP-compatible agent.

View on GitHub →

⚡

AI-Agent Skills

5 skill definitions with workflow guidance for core, advanced, industry, stakeholder, and emerging valuation domains.

Browse Skills →

What People Say

"I enthusiastically endorse Simon Mak as a phenomenal leader who masterfully blends the art of attentive listening with a motivational drive to propel their team towards excellence. He strikes an impressive balance between approachability and pushing for progress, fostering innovation and personal development."

Peter Pham

Head of Business Valuation

"Working with Simon on projects is the perfect combination of knowledge, experience and creativity. The short response time did not give me the feeling of working in different time zones. Looking forward to work on the next project."

Alfred Brandner

Luxembourg

Startup Valuation: A Comprehensive Guide

Companion Library

This site is the companion documentation for the Python library implementing 80+ formulas from the Startup Valuation textbook.

Quick Start

pip install startup-valuation

from startup_valuation.core import scorecard_valuation, vc_method_post_money
from startup_valuation.advanced import black_scholes

# Scorecard Method
result = scorecard_valuation(
    average_valuation=1_500_000,
    weights=[0.30, 0.25, 0.15, 0.10, 0.10, 0.05, 0.05],
    scores=[1.25, 1.50, 1.20, 0.75, 1.00, 0.90, 1.00],
)
print(f"Scorecard: ${result.value:,.0f}")  # $1,800,000

# Black-Scholes for real options
result = black_scholes(20_000_000, 5_000_000, 0.05, 0.40, 1.0)
print(f"Option value: ${result.value:,.0f}")  # $15,240,000

Book Chapters → Library Modules

Chapter	Topic	Library Module
1	Introduction to Startup Valuation	—
2	Probability, TVM, CAPM	probability, tv, capm
3	Core Valuation Methods	core
4	Advanced Methods	advanced
5	Comparables & Multiples	comparables
6–10	Specialized Topics	See textbook
11	Industry-Specific Models	saas, biotech, fintech, marketplace, hardware
12	International Valuation	international
13	Stakeholder Analysis	stakeholders
14	Emerging Methods	emerging
15	Conclusion & Best Practices	—

Features

• 80+ valuation formulas across 14 modules covering every method in the textbook
• Typed Python API with structured ValuationResult returns (value + assumptions + sensitivity)
• MCP Server exposing all calculations as tools for AI agents (Claude, OpenCode, etc.)
• AI-Agent Skills with workflow guidance for 5 valuation domains
• Every function tested against textbook example values

Modules

Module	Methods	Chapter
probability	Expected value, joint probability, Poisson	2
tv	PV, NPV, annuity	2
capm	CAPM, portfolio beta, startup-adjusted	2
core	Scorecard, Berkus, Risk Factor, VC Method	3
advanced	Black-Scholes, Binomial, Monte Carlo, Scenario	4
comparables	Multiples, regression-adjusted	5
saas	LTV, CAC, NRR, Magic Number, Rule of 40	11
biotech	rNPV, decision tree, peak sales, pipeline	11
fintech	Payment revenue, lending, network effects	11
marketplace	GMV, take rate, liquidity, network density	11
hardware	TRL-adjusted, break-even, P-weighted DCF	11
international	PPP, CRP, currency-adjusted DCF	12
stakeholders	Dilution, OPM, PWERM, liquidation	13
emerging	SAFE, MV=PQ, ESG, Metcalfe's Law	14

MCP Server

cd mcp_server && python server.py

Connect with any MCP-compatible AI agent. All 60+ valuation tools are available.

AI-Agent Skills

Copy the skills/ directory to your agent's skills folder. Available skills: - valuation-core — Scorecard, Berkus, VC Method, Risk Factor - valuation-advanced — Black-Scholes, Monte Carlo, Scenario Analysis - valuation-industry — SaaS, Biotech, Fintech, Marketplace, Hardware - valuation-stakeholder — Dilution, OPM, PWERM, Liquidation - valuation-emerging — SAFE, Crypto, ESG, Network Effects - valuation-foundations — Probability, TVM, CAPM, Comparables, International

Development

pip install -e ".[dev]"
pytest --cov=startup_valuation --cov-report=term-missing
ruff check .

License

MIT