A virtual assistant receives natural language interpretation hypotheses for user queries, determines entities and attributes from the interpretations, and requests data from appropriate data sources. A cost function estimates the cost of each data source request. Cost functions include factors such as contract pricing, access latency, and data quality. Based on the estimated cost, the virtual assistant sends requests to a plurality of data sources, each of which might be able to provide data necessary to answer the user query. By including user credits in the cost function, the virtual assistant provides better quality of results and answer latency for paying users. The virtual assistant minimizes latency by answering using data from the first responding data source or provides a latency guarantee by answering with the most accurate data received by a deadline. The virtual assistant measures data source response latency and caches responses for expensive requests.