Piggybacking off @Mark_Bailey's response here. Yes, the Confidence Interval of the prediction for a continuous Y vs a continuous X in Graph Builder uses a 95% level by default, and the interval width is smaller at the mean of the regression (the midpoint of the fitted line) than at the ends of the regression line. This confidence interval on the regression line is sometimes referred to as a "hotelling" confidence band, and you can have JMP compute and save these calculated confidence limits boundaries for you in Graph Builder (or in the Bivariate Platform, where they should be exactly the same). As mentioned, the formulas use a 'quadratic form' and this is reflected in the vector quadratic function saved out in column formulas to the JMP data table for these limits.
For a continuous Y on a nominal (or ordinal) X in Graph Builder, I'd like to point out that JMP also uses a 95% level by default. Here, if using the Points, summarizing on the Mean (Summary Statistic), and picking Confidence Interval (Error Interval), then JMP performs a classical "t-statistic based" interval estimation calculation where the CI for each level is calculated independently. The formula is given in most introductory statistical textbooks, and it looks like this:
(image courtesy of JMP STIPS Decision Making With Data Course Module Constructing Confidence Intervals)
where t is the t-statistic at: 1 minus α Confidence level and at n minus 1 degrees of freedom (where n is sample size),
S is the standard deviation, and X-bar is the mean.
For more information, see the Decision Making with Data Module of JMP's free online statistics course, STIPS (at jmp.com/statisticalthinking).