Cosolvent
Cosolvent is an open-source platform designed to democratize access to AI-powered market making technology. Built specifically for “thin markets”—where buyers and sellers are scattered and struggle to find each other … Cosolvent provides a complete foundation for anyone wanting to explore LLM+RAG automation in specialized trading environments and offers the following key features:
Intelligent Profile Creation: Users can build profiles by uploading existing documents—specifications, certifications, product descriptions, or any relevant materials. Cosolvent’s AI automatically extracts and structures this information into searchable, matchable profiles with a consistent look and feel without requiring users to fill out complex forms or learn new systems.
Curated Industry Context: Each market implementation includes a carefully assembled library of industry-specific information—standards, regulations, terminology, and best practices—that provides essential context for accurate matching and relevant responses.
Integrated AI Search: The platform combines user profiles with industry knowledge through advanced LLM+RAG technology, enabling sophisticated queries that understand nuanced requirements and deliver contextually appropriate matches and recommendations.
Open Source Commitment: Released under the MIT license, Cosolvent is freely available on Github for modification, deployment, and commercial use. Our goal is to empower developers, entrepreneurs, and organizations worldwide to create more efficient markets, particularly in underserved sectors and developing economies where improved market access can drive meaningful economic impact.
Posts
Unlocking Trillions in Thin Market Value
The global opportunity for AI-driven matching platforms like Cosolvent to unlock value in thin markets and long tail B2B segments represents a $3-5 trillion annual transaction value opportunity, with potential to capture $200-400 billion in incremental revenue through improved market efficiency and enabling previously impossible transactions. Thin Markets Create Massive
Cosolvent as an Experiment: A Playground for Thin Market Innovation
Cosolvent is not a finished product. It’s an experiment—an open-source playground designed to test the possibilities and limits of AI-enhanced market matching. The Unknowns: These are open questions. Cosolvent is being released not as a polished solution, but as a testbed where developers, users, and researchers can explore answers together.
The Case for Cosolvent in Enterprise Hiring
Thin Market Characteristics Assessment Information Asymmetry: HIGH Complex Matching Criteria: VERY HIGH Scattered Participants: MODERATE Economic Viability Analysis Transaction Value vs. Platform Costs: STRONG Friction Cost Reduction: VERY HIGH Risk Mitigation Value: EXTREMELY HIGH Revenue Model Potential Pricing Power: STRONG Market Expansion: SIGNIFICANT Implementation Considerations Platform Development ROI: FAVORABLE Market
100 Thin Markets for Cosolvent
It’s early days, but Cosolvent’s approach to using AI to facilitate thin markets has a vast range of potential applications. Here is a list of 100 potential uses. Cosolvent probably won’t be asked to address many of them, but its possible that it might help with most of them.
The Risks of LLM+RAG: Hallucinations, Missed Data, and How Cosolvent Mitigates Them
As powerful as Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) can be, they come with real risks—especially when applied to market matching in thin and high-stakes environments. Common Risks: How Cosolvent Minimizes These Risks: Cosolvent’s approach blends automation with safeguards—helping users get the benefits of AI while minimizing the
Creating Trust in Thin Markets
When Nobel Prize winner Alvin Roth identified “thin markets” as a fundamental economic challenge, he highlighted a problem that has plagued commerce for centuries. These markets, where buyers and sellers are widely scattered and have difficulty finding each other, represent enormous untapped potential. Yet even when participants do connect, a