your startup.
Seven free tools for founders — find out whether you can bootstrap it at all, work out what your recurring revenue really is, check whether you're ready to raise, size the round and what it buys, model what it costs you in ownership, split the equity between co-founders defensibly, and find the way into an investor network that fits you.
Open the toolsBootstrap or raise is not a matter of temperament. Whether a company can fund itself out of its own revenue is mostly a property of the business — how soon it can charge, how much of each euro survives, how much has to be spent before anything can be sold, and whether the market gives you the time. First the conditions, then the same question in cash.
The binding constraint is payment terms. Upfront payment, a deposit, or annual billing in advance. Bhidé: watch cash, not profit — a profitable company can still die of payment terms.
Left axis: monthly flows in k€. Cash has its own scale — as a running balance it would otherwise flatten every flow line against the floor.
The arithmetic is trivial. What is not, and what costs founders credibility in diligence, is deciding what may be counted. ARR is contracted recurring revenue annualised — not last month times twelve. Setup fees, services and usage above a committed floor are revenue and are not ARR, and an investor will strip them out whether or not you did.
| Plan | Price | Billed | Customers | MRR | ARR | |
|---|---|---|---|---|---|---|
| 6.0 k€ | 72.0 k€ | |||||
| 13.2 k€ | 158.4 k€ | |||||
| 9.0 k€ | 108.0 k€ | |||||
| Total | 28.2 k€ | 338.4 k€ | ||||
Two companies with identical growth can have completely different bridges, and the bridge is what the next round is priced on. Retention counts the existing base only; new business is not retention.
ARR carried forward at the growth the current bridge implies — 9.4 % a month. A straight line off one month, not a forecast: the point is what today's retention compounds to, not what will happen.
Net revenue retention is 98 %. The base shrinks by itself, so every month of growth has to be bought again from new business — a bucket that has to be filled faster than it drains.
Tick what you already have. The model scores five readiness dimensions from the fundraising literature, names your binding constraint, and ranks what to fix by leverage — not by what's easiest.
Readiness tells you whether to start. This tells you who to aim at. Rate how much each criterion matters to you (1 = irrelevant, 5 = essential) and the model ranks the investor archetypes that fit.
One individual who can write a meaningful first cheque and keep writing. Anchors the round and spares you re-starting from zero next time.
Watch: Ask directly what they have reserved for follow-on. “I usually follow on” is not a reserve.
Someone who has built in your market and whose address book contains your customers. Their introductions are worth more than their money.
Watch: Agree what “helping” means before the cheque — customer intros, or advice you didn't ask for.
A recognisable investor whose participation makes the next conversation easier. You are buying a credential as much as capital.
Watch: A famous name with a small cheque can still anchor your round — but only if they let you use it publicly.
Individual angels and solo GPs who can say yes without a partner meeting. The fastest path to a first close and to momentum.
Watch: Speed cuts both ways — a fast yes from someone who did no diligence is a weaker signal to the next investor.
Chemistry over pedigree. Someone you would willingly call on the worst day of the company, which is when it actually counts.
Watch: Run reference calls with founders they backed who struggled, not the ones who did well.
| What you have | Feeds | Weight |
|---|---|---|
| I personally know investors who could write a cheque | Access | 1.00 |
| People vouch for me with investors | Access | 0.90 |
| People vouch for me with investors | Signals | 0.30 |
| I can name 3+ specific people who would vouch | Access | 0.70 |
| I can name 3+ specific people who would vouch | Process | 0.20 |
| I'm getting warm introductions | Access | 0.80 |
| I'm working existing contacts directly | Access | 0.50 |
| I meet investors at events | Access | 0.40 |
| I use investor platforms (OpenVC etc.) | Access | 0.30 |
| I do cold outreach (email / LinkedIn) | Access | 0.15 |
| I do cold outreach (email / LinkedIn) | Process | 0.20 |
| Revenue / MRR | Signals | 1.00 |
| Recognisable customers | Signals | 0.90 |
| Press / awards | Signals | 0.40 |
| A prior exit | Signals | 1.00 |
| A prior exit | Access | 0.40 |
| Accelerator / programme | Signals | 0.60 |
| Accelerator / programme | Access | 0.40 |
| Well-known advisors | Signals | 0.60 |
| Well-known advisors | Access | 0.40 |
| The raise target is defined | Clarity of the ask | 1.00 |
| I know which investors fit — stage, ticket, sector, region | Clarity of the ask | 0.80 |
| I know which investors fit — stage, ticket, sector, region | Process | 0.30 |
| I've considered grants / non-dilutive | Clarity of the ask | 0.30 |
| I'm testing different storylines | Clarity of the ask | 0.60 |
| I'm testing different storylines | Process | 0.20 |
| Teaser deck (2 minutes) | Materials | 1.00 |
| Pitch deck (15+ slides) | Materials | 0.80 |
| Read-deck to share after meetings | Materials | 0.70 |
| Data room with access control | Materials | 0.60 |
| Investor CRM set up | Materials | 0.40 |
| Investor CRM set up | Process | 0.60 |
| Investor Q&A document | Materials | 0.50 |
| Investor Q&A document | Clarity of the ask | 0.20 |
| Structured investor list | Process | 1.00 |
| I run advice-first conversations | Process | 0.60 |
| I run advice-first conversations | Access | 0.50 |
| I'm testing outreach channels | Process | 0.50 |
| Dimension: Access | Headline score | 0.30 |
| Dimension: Signals | Headline score | 0.25 |
| Dimension: Clarity of the ask | Headline score | 0.20 |
| Dimension: Materials | Headline score | 0.10 |
| Dimension: Process | Headline score | 0.15 |
Dimension weights are set by hand from the cited literature, not fitted to data — no dataset exists on which a readiness model like this has been estimated. Access carries the most because roughly 60% of deal flow arrives through networks; materials carry the least because the evidence says the formal plan matters less than founders assume.
Within a dimension the items are treated as substitutes, not a checklist: warm introductions, events and platforms are three ways into the same channel, so the score saturates — the three strongest items already put you at roughly 85%, and the rest fill in from there. Items you aren't expected to have at your stage, and items nobody can simply go and acquire (a prior exit), are left out of the target entirely and only ever count as upside. The typical range shown against your score is a design assumption on the same footing as the weights, not a measured benchmark. Treat the output as a structured argument about where your effort goes, not a prediction of whether you will raise.
Work the number backwards from the milestone the next round will expect: what the team costs, how long it takes, and what the plan needs on top for the parts that slip. The output is a round size and a use-of-funds breakdown you can put in front of an investor.
Means first: you say what team you want, the tool costs it. Honest when you don't yet know your conversion rates well enough for the arithmetic to mean anything.
The round has to outlast the raise that follows it, not end when that raise begins. You hit the milestone, then start talking to investors, and the money has to still be there when they take three months to decide.
The round closes with under two months to spare. Raises slip more often than they run early, so a little more margin here is cheap insurance.
Funds 21 months at full-team burn, inside the 18–24 month convention.
The sizing logic comes from the staging literature: a round buys runway to the next point where real information arrives, so the amount follows from the milestone rather than the other way round. The contingency exists because underestimating time and cost is one of the most replicated findings in behavioural research. The salary figures are DACH mid-market defaults you should override, and the runway and contingency ranges are conventions rather than measurements. Treat the output as a costed argument for a number, not a forecast.
What each round actually costs you in ownership. Model FFF, Angels & VCs across financing rounds, track dilution, build the cap table and simulate exits under different liquidation preferences.
| Round | Investment | Dilution % | Pre / Post-Money | ||
|---|---|---|---|---|---|
| Pre-Seed | 500 Tsd € | 15% | 2.8 Mio € / 3.3 Mio € | ||
| Seed | 2.0 Mio € | 20% | 8.0 Mio € / 10 Mio € | ||
| Series A | 8.0 Mio € | 20% | 32 Mio € / 40 Mio € | ||
| Series B | 25 Mio € | 18% | 114 Mio € / 139 Mio € | ||
| Series C | 60 Mio € | 15% | 340 Mio € / 400 Mio € | ||
| Series D | 150 Mio € | 13% | 1Mrd € / 1.2Mrd € |
| Stakeholder | Ownership | Share | Exit Proceeds | Multiple |
|---|---|---|---|---|
| FounderFounder 1 | 30.6% | 30.6% | 9.2 Mio € | — |
| FounderFounder 2 | 30.6% | 30.6% | 9.2 Mio € | — |
| ESOPESOP Pool | 6.8% | 6.8% | 2.0 Mio € | — |
| InvestorPre-Seed Investors | 12.0% | 12.0% | 3.6 Mio € | 7.2× |
| InvestorSeed Investors | 20.0% | 20.0% | 6.0 Mio € | 3.0× |
| Total | 100% | 30 Mio € | 12.0× | |
Das Multiple ist der Exit-Erlös geteilt durch das eingezahlte Kapital — as-converted, also ohne Liquidationspräferenz. Was eine Präferenz daran ändert, steht im Abschnitt darüber; bei einem Exit unter der Bewertung der letzten Runde weichen die beiden deutlich voneinander ab. Gründer und ESOP haben kein Geld eingezahlt, deshalb steht dort kein Multiple.
Roughly three quarters of founding teams split equally, usually within a month of starting. The research does not say that is wrong — plenty of equal splits are correct. It says that teams who arrived there by default rather than by argument were far likelier to be unhappy with it later, and much less able to change it once it mattered. So this makes the factors explicit and shows what they imply.
The outer ring is the agreed split. The inner ring is how much of it each founder would actually own if they walked in month 8 — the hollow part has not been earned yet and returns to everyone who stayed.
The common default: what you do from here outweighs what you brought. Commitment and responsibility carry most of the weight.
| Factor | Weight | Founder A | Founder B |
|---|---|---|---|
| The ideaWho brought it. Worth less than founders expect — an idea nobody executes is worth nothing, which is why this factor is usually weighted low. | |||
| Groundwork doneThe research, the plan, the first customer conversations — work already finished before anyone was paid. | |||
| Domain expertiseWhat each person knows that the venture cannot easily buy. The hardest factor to replace and often the most undervalued. | |||
| Commitment & riskFull-time or evenings, salary given up, money put in, what happens to them if it fails. Usually the heaviest factor, because it is the one that decides whether anything gets built. | |||
| Ongoing responsibilityWhat each person carries from here on. The split is about the future far more than about the past. | |||
| Name & months already in |
Founders hold their shares from day one. Vesting is the right the company keeps to buy back the part that has not been earned if someone walks. Pick who, and when.
Straight away — and this is the part most often misunderstood. Founders hold their full stake from day one and are shareholders immediately. Vesting runs in reverse: the company keeps the right to take back the portion you have not yet earned if you leave. Employee options work the other way round, granted now and vesting into existence later. So the number in the cap table is your whole stake from the start; what changes over four years is how much of it you would keep on the way out.
Four years with a one-year cliff, then monthly. That is the convention in both the US and Europe and holds across roles and seniority. Nothing vests before the cliff, and the cliff then pays out twelve months at once — the discontinuity is deliberate, because the co-founder who turns out not to be one usually becomes apparent inside the first year. Credit for work done before the company existed is negotiable and common where it was real; it simply starts the clock earlier.
It is the most common outcome by a distance — around three quarters of teams split equally. It is not a problem in itself, and the research does not say it is. What the data shows is that teams who arrived there by default rather than by argument were far likelier to regret it and much less able to change it later. The practical risk of an exact 50:50 is deadlock: two shareholders, no tiebreaker, and any decision needing a majority can simply stop. Teams that keep 50:50 usually name a tiebreaker somewhere else — a casting vote for one role, a third board seat, or a written escalation process — rather than shave the split to 51:49 for its own sake.
From a pool carved out before the round, which means it dilutes the founders and not the incoming investor — that ordering is worth negotiating, and is worth as much as several points of valuation. In Europe a pool of roughly 10 % at seed is typical, of which only 3–4 % tends to be handed out before the Series A and the rest is held back for the hires that follow. The pool is not a gift to employees so much as a budget you will spend recruiting.
Virtual shares, in nearly all cases. Real GmbH shares need notarisation for every transfer and real options create a tax event employees usually cannot pay for, so the standard instrument is a VSOP: a contractual right to a cash payout tied to company value at an exit, with the same four-year vesting and the same good-leaver and bad-leaver mechanics. Since a Federal Labour Court ruling in March 2025, bad-leaver clauses that forfeit options an employee has already vested are invalid — vested options count as earned compensation. Plans written before that ruling are worth re-reading.
It falls fast with each hire, because risk falls fast. A first engineer joining before there is a product or a salary is closer to a late founder than to an employee, and single-digit percentages are defensible; by the tenth hire the same role is usually a fraction of one percent. The honest question is not what the market pays but what someone is giving up — a pay cut and an unhedged bet on one company are what the equity is compensating, and where neither applies, cash is the better instrument.
Far less than advisors ask for and far less than founders expect: tenths of a percent, vesting over about two years, and only against a defined commitment — a set number of hours, specific introductions, a named problem. Advisor equity that vests for being on a list is the cheapest thing to give away and the most expensive to still be carrying at Series B. A short written agreement with a scope and a cliff solves nearly all of it.
Conventions, not law — and the German notes are specific to a GmbH. Anything you are about to sign is worth an hour of a lawyer who does this weekly; this is for knowing what to ask them.
The weighted-factor method cannot tell you the right answer, because there isn't one — it turns a disagreement about fairness into a disagreement about numbers, which is a great deal easier to have. Score each other rather than yourselves, do it separately first, and compare. Where you differ is the actual conversation.
A weighted, three-layer model built from the empirical fundraising literature. Toggle your attributes on the left. Click any node to see the evidence behind it.
Toggle attributes on the left, or pick a preset.
Weights are set by hand from the cited literature, not estimated on data — no dataset exists on which a model like this has been fitted. The mechanism layer comes from the papers; the wiring between layers is an interpretive synthesis. Treat the output as a structured argument, not a prediction.
Every entry answers the same three things: what it is, why it exists, and what it does to you. The third is what term sheets are quietest about — a clause is rarely hostile in itself, only in combination with a mediocre outcome, which is exactly the case nobody models before signing.
Peer-reviewed work and primary documents only. Where a term is a practitioner convention with no research behind it — most of the SaaS metrics are — the entry says so rather than dressing a blog post up as evidence. An invented citation would be worse than an honest “this is convention”.
Every number here is traceable to a paper or a government series, and each one carries what it measures — and what it does not — rather than hiding the caveat in a footnote. The figures that circulate loudest in this business mostly cannot be traced anywhere, so they are not here.
Read this one carefully. It counts every new employer establishment — overwhelmingly restaurants, shops and contractors. It is not a startup failure rate, and quoting it as one is the most common misuse of business statistics in a pitch deck.
Venture capital funds a vanishingly small number of companies and ends up owning a large share of the value. That is the arithmetic behind every question about market size — and behind an investor who likes you saying no.
Averaged across 1994–2022. Note what this counts: every new employer establishment, overwhelmingly restaurants, shops and contractors. It is not a startup failure rate, and using it as one is the most common misuse of business statistics in a deck — venture-backed companies are a tiny, unrepresentative slice of this population.
There is no unicorn map and no founder-archetype breakdown. The counts that circulate come from commercial trackers with proprietary inclusion rules that change without notice, and a map is precisely the format that lends unverifiable numbers an air of authority. If a figure could not be traced to a paper or a government series, it was left out rather than dressed up.