aicost.ai
VC/PE Diligence · AICost.ai cost decision engine

🔥 Is the growth efficient, or subsidised?

Compute the reported burn multiple, then reclassify inference disguised as growth spend back into COGS to expose the true burn multiple and gross margin.

Inputs

Enter what the company claims. Everything recomputes live.

After churn, not gross bookings. This is the denominator.
$
Net cash burn over the same window.
$
Used for the gross-margin reclassification.
$
As stated in the deck or data room.
%
Total AI/compute cost for the year.
$
The distortion knob: share mis-booked into S&M rather than COGS. Confirm against the GL.
%
Supply a model + volume to price inference vendor-exact instead of using the reported figure.
Optional workload.
Optional workload.
Optional workload volume.
Optional.
%
Optional.
%
Verdict
EFFICIENT

Burn multiple 1.2x is under 1.5x — efficient growth by 2026 Series A standards.

⇩ Download PDF memo View JSON All diligence tools
Burn multiple
1.2x
Reported gross margin
62%
True gross margin
62%
Margin erased
0 pts
Inference disguised as growth
$0
Share of burn that is subsidy
0%
ARR needed for an efficient 1.5x
$2,800,000
Inference basis
reported

Deal memo

Reported burn multiple is 1.2x (efficient) on $4,200,000 net burn against $3,500,000 net new ARR. Inference appears booked in COGS; gross margin holds at 62%. True margin is above the ~52% 2026 AI median. Ask for the GL classification of inference spend and the NRR of the cohort driving the ARR.

Questions for the founder

  1. Show the GL: how much inference/compute cost is booked in COGS vs sales & marketing vs R&D?
  2. What is net revenue retention on the cohort generating this net new ARR? (120%+ is the 2026 floor.)
  3. Is any usage sold at or below cost to drive logos — and what share of ARR is on such terms?
  4. What is the gross-margin trend over the last 4 quarters, net of all inference cost?
  5. What is the burn multiple trend quarter-over-quarter — is capital efficiency improving or decaying?
  6. Are there customer contracts with unlimited usage for fixed fees or price guarantees that cap expansion revenue?

Assumptions

  • Inference uses the reported annual figure ($700,000); supply a workload to price it vendor-exact. *
  • 0% of inference assumed mis-booked as growth/S&M — confirm against the GL. *
  • Burn multiple = net burn ÷ net new ARR over the same period; thresholds per 2026 Series A benchmarks.

Values marked * are analyst estimates rather than vendor-verified data.