Manual compliance checking between formal requirements and technical documentation is a time consuming task and prone to errors. Formal requirements are important statements that a product must satisfy, drawn from standards used in integrated logistics support. Technical documentation is the product manual an engineer checks against those requirements. This thesis investigates whether adding a reranking step to a retrieval augmented generation pipeline improves the accuracy of automated gap detection between the two. Two pipelines were compared, a standard RAG baseline and an extended RAG pipeline with Coherere ranking model. Both were evaluated against 15 requirements in English, drawn from MIL-STD-1388-2B, a United States military standard for logistic support analysis, and S3000L, an international standard published by ASD. The requirements were checked against a Swedish operator manual for the Hydronic M-IIheating system. The evaluation used context recall, faithfulness, verdict accuracy, and a domain expert review. The differences were marginal, but the reranking pipeline scored higher across all measures. Verdict accuracy increased by 6.7%, and the domain expert rated the reranking outputs higher on correctness (4.60 to 4.20 on a 1-5 scale). Reranking reduced retrieval noise and improved there levance of the context passed to the large language model, which led to more accurate compliance verdicts.