Various phases in the delivery of software services such as solution design, application deployment, and maintenance require analysis of the dependencies of software products that form the solution. As software systems become more complex and involve a large number of software products from multiple vendors, availability of correct and up-to-date system requirement information becomes critical to ensure proper functioning of managed and maintained software solutions. System requirement information, is mostly made available in unstructured formats from sources such as websites or product documents and are not amenable to programmatic analysis. In this paper, we motivate the benefits of capturing this information in a structured format for software service delivery, and present a dependency analysis system that collects and integrates software dependency/interoperability information from multiple unstructured sources using text mining techniques. Information hence collected, is used to support analytics useful in software service delivery. We report the results of our experiments on mining millions of web pages to collect dependency information for more than 700 software products.