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The inverse in crisp graph theory is a well-known topic. However, the inverse concept for fuzzy graphs has recently been created, and its numerous characteristics are being examined. Each node and edge in <i>m</i>-polar fuzzy graphs (<i>m</i>PFG) include <i>m</i> components, which are interlinked through a minimum relationship. However, if one wants to maximize the relationship between nodes and edges, then the <i>m</i>-polar fuzzy graph concept is inappropriate. Considering everything we wish to obtain here, we present an inverse graph under an <i>m</i>-polar fuzzy environment. An inverse <i>m</i>PFG is one in which each component’s membership value (MV) is greater than or equal to that of each component of the incidence nodes. This is in contrast to an <i>m</i>PFG, where each component’s MV is less than or equal to the MV of each component’s incidence nodes. An inverse mPFG’s characteristics and some of its isomorphic features are introduced. The <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mi>α</mi></semantics></math></inline-formula>-cut concept is also studied here. Here, we also define the composition and decomposition of an inverse <i>m</i>PFG uniquely with a proper explanation. The connectivity concept, that is, the strength of connectedness, cut nodes, bridges, etc., is also developed on an inverse <i>m</i>PF environment, and some of the properties of this concept are also discussed in detail. Lastly, a real-life application based on the robotics manufacturing allocation problem is solved with the help of an inverse <i>m</i>PFG.