Let $\mu$ be a measure on $2^\omega$ which doesn't have a least Turing degree.
This exists by Theorem 4.2 of
Day, Adam R.; Miller, Joseph S., Randomness for non-computable measures, Trans. Am. Math. Soc. 365, No. 7, 3575-3591 (2013). ZBL1307.03026.. Trans. Amer. Math.
Soc., 365:3575–3591, 2013.
Let $S$ be the class of infinite sequences of reals $X_i$ that are Martin-Lof random with respect to the infinite product measure of $\mu$, $$\mu\times\mu\times\dots$$ with a fixed randomness deficiency constant $c$.
This $S$ is pre-pointable because by the Law of Large Numbers each element of $S$ can compute a representation of $\mu$.
If $S$ is pointable, it implies something close to saying that $\mu$ has a least Turing degree after all: there is a representation of $\mu$ that all the randoms compute.
Then we may use a de Leeuw, Moore, Shannon, Shapiro / Sacks Theorem:
Computability by Probabilistic Machines
K. de Leeuw, E. F. Moore, C. E. Shannon & N. Shapiro
Journal of Symbolic Logic 35 (3):481-482 (1970)
for $\mu$ to the effect that if a real $A$ [in particular $A$ could be a representation of $\mu$ or $S$] is computed by all sequences of mutually $\mu$-randoms, then $A$ is computed by all representations of $\mu$.
This would be a generalization of a result for Bernoulli measures (which is are already infinite product measures) from
Kjos-Hanssen, Bjørn, Permutations of the integers induce only the trivial automorphism of the Turing degrees, ZBL06916706.
We also want a lemma to the effect that computing a representation of $\mu$ is equivalent to computing a representation of $S$. Computing a representation of $S$ from a representation of $\mu$ is I guess the familiar direction, similar to the case of Bernoulli measures. Computing a representation of $\mu$ from a representation of $S$ runs into the problem that some strings are dead ends and may mislead us. However we may again use a certain effectivity in the LLN to (nonuniformly) bound the rate of convergence and hopefully overcome this.