Ecosystem capital underwriting

Fund working builders.
Make every constraint visible.

Turn minimum viable checks and verified 90-day milestones into one exact, auditable support slate.

name, category, minimum_k, milestones, partnership_ready
Required categories
Verified milestones-
Builders funded-
Capital allocated-
Categories-
Pass 1 waitingPass 2 waiting0 binary choices

Exact support slate

Load proposal evidence to begin.

The selected and excluded proposals will appear here with capital, milestone, category, and partnership evidence.

Decision boundaryMilestones are proposal evidence, not predicted returns. Review diligence, legal obligations, and execution risk outside this model.

Conviction becomes useful when assumptions can be challenged.

Minimum viable checks prevent partial allocations from pretending to fund a launch.

Category floors keep one attractive vertical from consuming the whole ecosystem budget.

The second pass broadens builder support only after preserving the maximum verified milestone outcome.

Trace binary minimum checks and the two-pass allocation objective

Read the explanation

This saved allocator solves a hypothetical binary-choice model, not a return forecast or a verification of proposed builders. Its five sample minimum checks total one hundred fifty thousand dollars. The sample budget is one hundred ten thousand. Both bars use three pixels per thousand dollars. The model must exclude at least one proposal because checks are indivisible; it cannot simply reduce every grant to fit. Required categories and a partnership-ready floor also remain hard constraints. At the sample constraints, the local solver first maximizes verified milestone counts and returns thirteen. One feasible slate is ForgePay, LearnLoop and MarketMesh: one hundred five thousand dollars and thirteen milestones. Another is LearnLoop, MarketMesh, CivicLens and GuildOS: one hundred ten thousand dollars and thirteen milestones. Both bars use thirty pixels per milestone. The source treats the supplied milestone numbers as evidence inputs; their factual accuracy is not checked by the optimization. The source then runs a second integer solve. It fixes the first milestone optimum at thirteen and maximizes the number of funded builders. The second slate wins with four builders instead of three. Both bars use one hundred pixels per builder. The actual sample output allocates all one hundred ten thousand dollars with zero slack and three partnership-ready selected builders. This is a lexicographic two-pass preference, not a blended score or a predicted investment outcome.

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