For a sequence $(x_n)$ we have the following implications:
$$
\begin{matrix}
(x_n)_n \text{ convergent} & \implies & (x_n)_n \text{ Cauchy} \\
\Downarrow & & \Downarrow \\
(\Vert x_n \Vert )_n \text{ convergent} & \implies & (\Vert x_n \Vert )_n \text{ Cauchy} \\
\end{matrix}
$$
(and the “horizontal” implications are equivalences if $X$ is complete).
But none of this implies that the corresponding series $\sum x_n$ converges at all, a simple counter-example is a constant non-zero sequence.
The series $\sum x_n$ is convergent if the sequence $(s_n)_n$ of partial sums $s_n = \sum_{k=1}^n x_k$ is convergent. With $S_n = \sum_{k=1}^n \Vert x_k \Vert$ we have
$$
\begin{matrix}
\sum \Vert x_n \Vert \text{ convergent} & \iff (S_n)_n \text{ convergent} & \implies & (S_n)_n \text{ Cauchy} \\
& & & \Downarrow \\
\sum x_n \text{ convergent} & \iff (s_n)_n \text{ convergent} & \implies & (s_n)_n \text{ Cauchy} \\
\Downarrow \\
\lim_{n\to \infty} x_n = 0
\end{matrix}
$$
If $X$ is complete then the horizontal implications are equivalences, to that
$$
\sum \Vert x_n \Vert \text{ convergent} \implies \sum x_n \text{ convergent} \, .
$$
But again, $(x_n)$ being Cauchy (or convergent) does not imply that $\sum x_n $ is convergent (conditionally or absolutely).