diff --git a/doc/source/getting_started/index.rst b/doc/source/getting_started/index.rst
index 428c670c..5e35caf5 100644
--- a/doc/source/getting_started/index.rst
+++ b/doc/source/getting_started/index.rst
@@ -5,7 +5,8 @@ Getting started
 ===============
 
 PyTwin provides Pythonic access to twin runtimes that were generated using
-`Ansys Twin Builder and Ansys Twin Deployer <https://www.ansys.com/products/digital-twin/ansys-twin-builder>`_.
+`Ansys Twin Builder <https://www.ansys.com/products/digital-twin/ansys-twin-builder>`_ and
+`Ansys TwinAI <https://www.ansys.com/products/digital-twin/ansys-twinai>`_.
 
 PyTwin supports twin runtimes generated using 2023 R1 and later.
 
@@ -22,7 +23,7 @@ For twin runtimes generated with 2023 R1 SP1 and later versions:
 - if the TWIN file is exported as 'unlicensed', no license is needed to use PyTwin
 
 Both the features ``twin_builder_deployer`` and ``twin_runtime`` are included in the
-Twin Deployer license file. Here is how you define the environment variable for specifying the location of
+TwinAI license file. Here is how you define the environment variable for specifying the location of
 Ansys License Manager:
 
 .. code::
@@ -38,7 +39,7 @@ generated by `Ansys Twin Builder <https://www.ansys.com/products/digital-twin/an
 TWIN files are generally made up of several types of models, including system-level models, ROMs
 (reduced order models), third-party models, and FMU (Functional Mock-up Unit) files. Each of these
 models can have specific runtime dependencies. For example, Modelica models cross-compiled with
-Twin Deployer on Ubuntu 20.04 have a dependency on libgfortran5.
+TwinAI on Ubuntu 20.04 have a dependency on libgfortran5.
 
 When executing twin runtimes through PyTwin on a specific environment, all dependencies of the
 twin runtimes, including the ones of their constitutive models, must be properly installed
diff --git a/doc/source/index.rst b/doc/source/index.rst
index 2fff3068..f95d3ec2 100644
--- a/doc/source/index.rst
+++ b/doc/source/index.rst
@@ -25,7 +25,7 @@ costs, and both gain and retain competitive advantages.
   :width: 800
   :alt: Ansys Digital Twins
 
-Ansys Twin Builder and Ansys Twin Deployer are open solutions that allow engineers to create
+Ansys Twin Builder and Ansys TwinAI are open solutions that allow engineers to create
 digital twins and export them in the form of deployable twin runtimes.
 
 What is PyTwin?
@@ -67,14 +67,14 @@ License
 PyTwin is licensed under the MIT license.
 
 PyTwin makes no commercial claim over Ansys whatsoever. This library
-extends the functionality of Ansys Twin Builder and Twin Deployer by adding
+extends the functionality of Ansys Twin Builder and Ansys TwinAI by adding
 a Pythonic interface to twin runtimes without changing the
 core behavior or license of the original software. The interactive
 control of twin runtimes through PyTwin may require a license of
-Twin Deployer depending on the case, see :ref:`getting_started` section for more information.
+Ansys TwinAI depending on the case, see :ref:`getting_started` section for more information.
 
-For more information on both Ansys Twin Builder and Twin Deployer, see
-`Ansys Twin Builder <https://www.ansys.com/products/digital-twin/ansys-twin-builder>`_
+For more information on both Ansys Twin Builder and Ansys TwinAI, see
+`Ansys Digital Twin <https://www.ansys.com/products/digital-twin>`_
 on the Ansys website.
 
 Project index
diff --git a/src/ansys/pytwin/evaluate/tbrom.py b/src/ansys/pytwin/evaluate/tbrom.py
index fdfd0ea7..5025b3e7 100644
--- a/src/ansys/pytwin/evaluate/tbrom.py
+++ b/src/ansys/pytwin/evaluate/tbrom.py
@@ -107,6 +107,7 @@ def _read_settings(filepath):
     namedselection = {}
     dimensionality = None
     name = None
+    outputname = None
     unit = None
 
     if "namedSelections" in data:
@@ -121,11 +122,11 @@ def _read_settings(filepath):
 
     if "name" in data:
         name = data["name"]
+        outputname = name.replace(" ", "_")
     if "unit" in data:
         unit = data["unit"]
 
     tbromns = dict()
-    outputname = name.replace(" ", "_")
 
     # Create list of name selections indexes
     for name, idsList in namedselection.items():