Building Thin Markets with AI.
A four-tool stack for diagnosing structural friction and deploying open-source matching infrastructure. Built on 50 years of practitioner experience.
A four-tool stack for diagnosing structural friction and deploying open-source matching infrastructure. Built on 50 years of practitioner experience.
From diagnosing structural friction to deploying open-source matching infrastructure.
A rigorous diagnostic tool cross-tabulating generic thin market challenges against five AI engineering primitives.
250 prospective thin markets across 12 sectors, each tagged with binding challenges and sponsor opportunities.
A multi-model AI synthesis system that forensically deconstructs the market physics of any company in ~5 minutes.
An MIT-licensed marketplace engine and curated context manager for building secure, AI-mediated transaction networks.
While Cosolvent and CommonContext are open source, testing a thin market requires realistic participants. ClientSynth is our proprietary simulation tool designed to flood a Cosolvent instance with synthetic, agentic buyers and sellers. It allows you to prove the market physics work before risking live participant capital.
Use the matrix as a pre-raise market-design diagnostic, request a marketmap of your own narrative as a stress-test, and use Cosolvent as a marketplace prototyping shortcut.
Use the catalog as a sourcing scaffold and portfolio-coverage map, and request marketmaps on specific deals to forensically assess thin-market challenges.
Standardize cohort vocabulary with the matrix, seed vertical theses from the catalog, and evaluate applicants on a consistent, evidence-based rubric.
Identify thin-market opportunities specific to your sector. For Canadian policy experts, ~250 catalogued scenarios are anchored in regulatory institutions, mapping where intervention could thicken markets.