Is it possible to get seek based parallel plan for distinct/group by?

An example from this question shows that SQL Server will choose a full index scan to solve a query like this:

select distinct [typeName] from [types]

Where [typeName] has a non-clustered, non-unique ascending index on it. His example has 200M rows but only 76 unique values. It seems like a seek plan would be a better choice with that density (~76 multiple binary searchs)?

His case could be normalized but the reason for the question is that I really want to solve something like this:

select TransactionId, max(MaxCreatedUtc) from TxLog group by TransactionId.

There is an index on (TransactionId, MaxCreatedUtc).

Re-writing using a normalized source (dt) does not not change the plan.

select dt.TransactionId, MaxCreatedUtc
 from [Transaction] dt -- distinct transactions
 cross apply
   (
        select MaxCreatedUtc from TxLog tl
         where tl.TransactionId = dt.TransactionId         
   ) ca

Running just the CA subquery as a Scalar UDF does show a plan of 1 seek.

select max(CreatedUtc) as MaxCreatedUtc from Pub.TransactionLog where TransactionID = @TxId;

Using that Scalar UDF in the original query seems to work but loses parallelism (known issue with UDFs):

select t.typeName, 
       Pub.ufn_TransactionMaxCreatedUtc(t.TransactionId) as MaxCreatedUtc
  from Pub.[Transaction] t

Rewriting using an Inline TVF reverts it back to the scan based plan.