Making thin markets
work better.

Nobel laureate Alvin Roth identified thin markets as a fundamental economic problem: markets where transactions are infrequent, matching is difficult, and beneficial exchanges fail to occur despite willing participants on both sides.

The DeeperPoint framework identifies two categories of forces that prevent markets from working: existential threats (risk, trust, regulation) that can prevent a market from forming at all, and resistance challenges (opacity, offering complexity, distance, cognitive overload) that reduce efficiency.

For centuries, overcoming these forces required a painful tradeoff: standardize to create thickness (destroying useful information) or preserve uniqueness to maintain relevance (fragmenting markets). AI dissolves this tradeoff.