Information technology (IT) service providers typically compete in a tender kind of process to win highly valued service contracts. The process starts with the client submitting a request for proposal (RFP) document. The service providers prepare s solution that would fulfill the requirements from the RFP. However, this solution is typically prepared manually, requiring intensive resource preparation that can take weeks or months. In this work-in-progress paper, we propose a two-step automated end-To-end solution methodology to prepare a competitive solution. The first step involves taking the client's requirements and mapping them to the optimal set of the provider's offerings and their attribute values that cover such client requirements at a minimum cost. In the second step, market benchmarks are applied to compute the pricing of chosen offerings. Sometimes these benchmarks are unknown for particular offerings provided in some geographies world-wide. Therefore, we propose an approach for inferring these unknown benchmarks along with a confidence score. We apply our overall methodology to real data of one of the world's largest IT service providers and show that it is both more efficient and more effective than manual solutioning, thus increasing win rates for the provider.