Context and motivation. In today’s fast-paced software development, stakeholders expect frequent deployments that incorporate the newest requirements and needed adaptations. Such fast pace poses significant pressure on site reliability engineers (SRE), who ensure software quality while managing transitions through stages (testing, development, or production stages). Problem. The primary challenge SRE face is the amount of ubiquitous data ranging from requirements to test results (often) interconnected from the different software development phases (requirements elicitation, development, testing, and deployment) that requires effective analysis to inform staging decisions. Solution. This challenge has motivated us to establish the AI-SQUARE innovation project; in which we envision the creation of an intelligent end-to-end software staging support platform for decision making and feedback. We propose to leverage the use of knowledge graphs for analyising requirements from varios data sources and faciliate quality analysis from agreggated data. Results and conclusions. In this poster & tool paper, we share our progress on designing the knowledge graph that supports the AI-SQUARE platform, enhancing intelligent agents and supporting site reliability engineers during software staging. We share our vision and open challenges in implementing and evaluating our knowledge graph.