Conditional prediction markets for capital allocation and decision-making
Butter builds conditional markets that help organisations allocate resources more effectively. Instead of relying on committees, it uses market signals — people putting money behind beliefs — to surface which grants, programs, or bets are likely to generate the highest impact.
These "conditional funding markets" sit at the intersection of prediction markets and budgeting, turning decision-making into an incentive-aligned process that can scale with communities and treasuries.
How conditional markets outperform committees and event markets
A conditional market asks not "will X happen?" but "will X happen if we do Y?" — and prices both branches separately. That structure is more capital efficient than an event market (capital isn't trapped waiting for a single outcome) and more honest than a committee (incentives are aligned with being right, not with social consensus). We made the full argument in Better Decisions with Butter, and conditional markets are a core primitive in our Trust Infrastructure thesis.
Why LAVA invested in Butter
Capital allocation is a hard problem in crypto and beyond — especially when outcomes are uncertain and coordination is messy. Butter offers a mechanism that is more legible, more competitive, and harder to game than most committee-driven processes.
Conditional markets are also just more interesting, and more capital efficient, than event markets. They are much closer to the "truth engine" that prediction markets are often sold as. We love backing technical founders building with principles, rather than just following the most recent, popular trend.