Trends such as the massive increase in information available via electronic networks, the use of on-line product data by distributed concurrent engineering teams, and dynamic supply chain integration for electronic commerce are placing severe burdens on traditional methods of information sharing and retrieval. Sources of information are far too numerous and dynamic to be found via traditional information retrieval methods, and potential consumers are seeing increased need for automatic notification services. Matchmaking is an approach based on emerging information integration technologies whereby potential producers and consumers of information send messages describing their information capabilities and needs. These descriptions, represented in rich, machine-interpretable description languages, are unified by the matchmaker to identify potential matches. Based on the matches, a variety of information brokering services are performed. We introduce matchmaking, and argue that it permits large numbers of dynamic consumers and providers, operating on rapidly-changing data, to share information more effectively than via traditional methods. Two matchmakers are described, the SHADE matchmaker, which operates over logical and structured text languages, and the COINS matchmaker, which operates over free text. These matchmakers have been used for a variety of applications, most significantly, in the domains of engineering and electronic commerce. We describe our experiences with the SHADE and COINS matchmaker, and we outline the major observed benefits and problems of matchmaking.