We study the design of mechanisms by an intermediary that generate information for a sender and for a receiver about an unknown attribute of the sender. The sender is initially privately, but imperfectly, informed about her attribute and the receiver takes an action based on posterior beliefs about the sender’s attribute and the sender’s belief about the attribute. The design of the mechanism therefore confronts both incentive compatibility constraints (for the sender) and obedience constraints (for the receiver). We characterize profit-maximizing mechanisms when the intermediary contracts with the sender and we specialize to two applications: the design of college-admissions tests and the optimal use of consumer data on a digital market platform.