In this work, we have demonstrated the efficiency and flexibility of a k-d tree-based insertion algorithm, focusing on its dynamic batch variant. Our benchmarks show that insertion times for a wide range of solvent molecules scale nearly linearly with the total number of inserted molecules, significantly outperforming naive, one-by-one tree-reconstruction strategies. These results suggest that dynamic batch-based k-d insertion is a practical method for rapidly building large molecular systems. Future efforts will aim to integrate this approach into widely available simulation packages and expand the benchmarks to include more complex, flexible, and anisotropic molecular species.