See exactly what you get

Real-shaped examples of a full Viability Model. Switch profiles to see how the same engine reads a healthy business, a leaky one, and a founder raising — the score, the plain-English verdict, and the numbers underneath.

A founder just out of the gate — near pre-revenue, tight cash. See how the model reads the earliest stage.

59 /100

Viability score

Fragile

It can work, but key levers are weak. Tighten them before pushing growth.

At risk
0–39
Fragile
40–59
On track
60–79
Strong
80–100
Survivali
22
Unit economicsi
100
Retentioni
100
Growthi
100
Efficiencyi
100

Orientative, not absolute — weighted from survival, unit economics, retention, growth and efficiency against early-stage SaaS ranges (§9). Read it by stage, not as a grade.

What this means

In short: at this pace your business runs out of cash around month 7 — before it can pay for itself. That's the headline to fix: you need more runway, faster revenue, or lower spending. The good news is you can see exactly how much, and you have time to act.

Your biggest problem is runway. On the current path your cash runs low around month 7, before the business covers its own costs. Everything else matters less until you close that gap.

On the per-customer maths: it costs about €17 to win a customer, and each one is worth roughly €1,333 over their lifetime — about 80 to 1. Healthy is 3 to 1 or better, so there's room, but you're in workable territory.

What to focus on first: extend your runway before month 7. Three levers — raise more, grow revenue faster, or cut spending. The first buys time; the other two fix the business. Knowing your number turns a vague worry into a plan.

Summary

Runwayi

5.6 months

Final MRRi

14,775 €

Avg MoM growthi

11%

Annual NRRi

100%

Unit economics & burn

ARPAi

50 €

LTVi

1,333 €

CACi

17 €

LTV : CACi

80.0

CAC paybacki

0.4 months

Monthly net burni

2,134 €

Burn multiplei

Profitable

Rule of 40i

>100

Magic numberi

>10

Quick ratioi

3.0

Founder dilutioni

0%

Post-moneyi

0 €

Dimmed: scale-up metrics (Rule of 40, magic number, quick ratio) — more relevant once you are past early traction. Your paid model shows them in full.

Included: an AI second opinion

Your model ships with a prompt calibrated to your exact numbers. Paste it into ChatGPT or Claude — it is locked to your figures and told not to invent or recompute anything, just judge them like a skeptical advisor:

You are a skeptical, experienced pre-seed/seed SaaS advisor — think a sharp fractional CFO who has seen hundreds of models. Below is my startup's financial model as JSON. These numbers are ALREADY computed by a deterministic engine: do NOT invent, recompute or "correct" any figure — only interpret what's there. Be brutally honest, no flattery, no hype.

Give me, concise and specific:
1. Verdict — is this default-alive? The single biggest risk, in one line.
2. Red flags, ranked — what would worry an investor or could kill the business.
3. What's genuinely strong (don't pad this).
4. The 3 most important things to fix or test next — each with the specific number to target.
5. If I were raising: the 3 hardest questions a VC would ask about these numbers.

Context so you judge fairly: these are early-stage estimates with deliberate simplifications — cash ≈ recognized MRR (annual/upfront billing not modeled), LTV uses logo churn capped at 60 months and ignores expansion, no taxes or balance sheet. Judge at pre-seed/seed standards, not mature-company standards.

Here is the model:
{
  "meta": { "sector": "…", "stage": "…" },
  "revenue": { "mrr_final": …, "logo_churn": …, "nrr": … },
  "unit_economics": { "ltv": …, "cac": …, "ltv_cac": … },
  "runway": { "months": …, "zero_cash": … }
}
🔒 Your full model, as JSON, goes here

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These are illustrative example profiles, not a specific company's private data. Your model is built from your own numbers.

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Illustrative example models. Estimates for information only — not financial advice.