Value a Private Company
Estimate the fair market value of a private company before IPO by breaking it into business segments and forecasting each one independently. Numeric forecasting produces probability distributions per segment, which you sum for a bottom-up valuation.
Here, we build a sum-of-the-parts valuation for SpaceX ahead of its $1.75 trillion IPO across seven business segments.
Add FutureSearch to Claude Code if you haven't already:
claude mcp add futuresearch --scope project --transport http https://mcp.futuresearch.ai/mcp
Start by identifying the business segments:
SpaceX has filed for IPO at $1.75 trillion. Break SpaceX into its
major business segments and forecast the fair market value of each
in billions USD. Include Starlink (consumer, enterprise, direct-to-cell),
Falcon, Starship, xAI/Grok, and government/defense.
Claude calls FutureSearch's forecast MCP tool in numeric mode, one row per segment:
Tool: futuresearch_forecast
├─ data: [{"question": "What is the fair market value of Starlink Consumer?", ...},
│ {"question": "What is the fair market value of xAI / Grok?", ...},
│ {"question": "What is the fair market value of Starship?", ...},
│ ... ]
├─ forecast_type: "numeric"
├─ output_field: "fair_value"
├─ units: "billions USD"
└─ context: "Estimate the standalone fair market equity value of this SpaceX business segment as of April 2026."
→ Submitted: 7 rows for numeric percentile forecasting.
Session: https://futuresearch.ai/sessions/...
Tool: futuresearch_progress
→ Running: 2/7 complete, 5 running (180s elapsed)
...
Tool: futuresearch_progress
→ Completed: 7/7 (0 failed) in 420s.
Tool: futuresearch_results
→ Saved 7 rows with fair_value_p10 through fair_value_p90 columns.
Then ask Claude to sum the parts and compare to the IPO price:
Sum the median values across segments, adjust for cash and debt,
and compare to the $1.75T IPO target. What premium is the IPO
asking over fair value?
Add the FutureSearch connector if you haven't already. Then ask Claude:
SpaceX has filed for IPO at $1.75 trillion. Break it into major business segments and forecast the fair market value of each in billions USD. Then sum the parts and compare to the IPO price.
Go to futuresearch.ai/app and enter:
SpaceX has filed for IPO at $1.75 trillion. Break it into major business segments and forecast the fair market value of each in billions USD. Then sum the parts and compare to the IPO price.
pip install futuresearch
export FUTURESEARCH_API_KEY=your_key_here # Get one at futuresearch.ai/app/api-key
import asyncio
import pandas as pd
from futuresearch.ops import forecast
segments = pd.DataFrame([
{
"question": "What is the fair market equity value of Starlink Consumer Broadband?",
"background": "9.2M subscribers, ~$10B revenue. Satellite internet for residential customers.",
},
{
"question": "What is the fair market equity value of xAI / Grok?",
"background": "Merged into SpaceX at $250B in Feb 2026. ~$1.7B/yr revenue, ~$5.8B/yr losses.",
},
{
"question": "What is the fair market equity value of Starship Commercial Launch?",
"background": "Pre-revenue. Fully reusable rocket targeting 10-100x cost reduction vs Falcon.",
},
{
"question": "What is the fair market equity value of Starlink Enterprise/Maritime/Aviation?",
"background": "~$2-3B revenue at higher per-customer prices than residential.",
},
{
"question": "What is the fair market equity value of SpaceX Government/Defense?",
"background": "~$22B contract backlog across Starshield, NASA HLS, NSSL, and classified programs.",
},
{
"question": "What is the fair market equity value of Falcon 9/Heavy Launch Services?",
"background": "~$5B revenue. ~60-70% of global orbital launches. Mature and cash-generative.",
},
{
"question": "What is the fair market equity value of Starlink Direct-to-Cell?",
"background": "Pre-revenue. $17-19B in EchoStar spectrum licenses for satellite-to-smartphone.",
},
])
async def main():
result = await forecast(
input=segments,
forecast_type="numeric",
output_field="fair_value",
units="billions USD",
context="Estimate standalone fair market equity value as of April 2026.",
)
df = result.data
sotp_median = df["fair_value_p50"].sum()
cash_minus_debt = 11.6 - 15 # $11.6B cash, ~$15B debt
equity_value = sotp_median + cash_minus_debt
ipo_target = 1750
print(f"SOTP segment total: ${sotp_median:.0f}B")
print(f"Equity value: ${equity_value:.0f}B")
print(f"IPO target: ${ipo_target}B")
print(f"Premium: {(ipo_target / equity_value - 1) * 100:.0f}%")
asyncio.run(main())
FutureSearch forecast each of seven business segments independently:
| Segment | Median Value | Key Driver |
|---|---|---|
| Starlink Consumer | $380B | 9.2M subscribers, ~38x revenue |
| xAI / Grok | $258B | Anchored by $250B merger price; $1.7B revenue vs $5.8B losses |
| Starship Commercial | $170B | Pre-revenue, pure option value on 10-100x cost reduction |
| Starlink Enterprise | $147B | Higher per-customer revenue than residential |
| Government / Defense | $123B | $22B contract backlog |
| Falcon 9/Heavy | $100B | Mature, cash-generative, ~65% of global orbital launches |
| Starlink Direct-to-Cell | $75B | Pre-revenue, backed by $17-19B in spectrum licenses |
Sum-of-the-parts: $1,253B in segments + $11.6B cash − $15B debt = ~$1,250B fair value. The $1.75T IPO target represents a 29% premium over the median SOTP estimate.
The gap isn't irrational. The SOTP method sums independent medians, but IPO pricing reflects correlated upside: if investors are bullish on Starlink, they're simultaneously bullish on Starship, xAI, and defense. Taking the 75th percentile across all segments brings the total to ~$1,675B, close to the target.
Starlink in all three forms (consumer, enterprise, direct-to-cell) accounts for $602B — 48% of segment value. Physical assets (satellites, launch pads, factories) are worth roughly $46B, or 2.6% of the IPO price. Nobody is buying SpaceX for its factories.
The full analysis is in A $1.75 Trillion IPO Would Be Overpaying 30% for SpaceX.
Built with FutureSearch. See the forecast documentation for all parameters and output formats. Related guides: Turn Claude into an Accurate Forecaster, Find Profitable Polymarket Trades, Forecast Outcomes for a List of Entities.