We revisit the Heaviest Induced Ancestors (HIA) problem that was introduced by Gagie, Gawrychowski, and Nekrich [CCCG 2013] and has a number of applications in string algorithms. Let $T_1$ and $T_2$ be two rooted trees whose nodes have weights that are increasing in all root-to-leaf paths, and labels on the leaves, such that no two leaves of a tree have the same label. A pair of nodes $(u, v)\in T_1 \times T_2$ is \emph{induced} if and only if there is a label shared by leaf-descendants of $u$ and $v$. In an HIA query, given nodes $x \in T_1$ and $y \in T_2$, the goal is to find an induced pair of nodes $(u, v)$ of the maximum total weight such that $u$ is an ancestor of~$x$ and $v$ is an ancestor of $y$. Let $n$ be the upper bound on the sizes of the two trees. It is known that no data structure of size $\tilde{\mathcal{O}}(n)$ can answer HIA queries in $o(\log n / \log \log n)$ time [Charalampopoulos, Gawrychowski, Pokorski; ICALP 2020]. This (unconditional) lower bound is a $\operatorname{polyloglog} n$ factor away from the query time of the fastest $\tilde{\mathcal{O}}(n)$-size data structure known to date for the HIA problem [Abedin, Hooshmand, Ganguly, Thankachan; Algorithmica 2022]. In this work, we resolve the query-time complexity of the HIA problem for the near-linear space regime by presenting a data structure that can be built in $\tilde{\mathcal{O}}(n)$ time and answers HIA queries in $\mathcal{O}(\log n/\log\log n)$ time. As a direct corollary, we obtain an $\tilde{\mathcal{O}}(n)$-size data structure that maintains the LCS of a static string and a dynamic string, both of length at most $n$, in time optimal for this space regime. The main ingredients of our approach are fractional cascading and the utilization of an $\mathcal{O}(\log n/ \log\log n)$-depth tree decomposition.