diff --git a/.github/workflows/sdk-release.yml b/.github/workflows/sdk-release.yml
new file mode 100644
index 00000000..70e32a04
--- /dev/null
+++ b/.github/workflows/sdk-release.yml
@@ -0,0 +1,82 @@
+name: Build Skyvern SDK and publish to PyPI
+
+on:
+  release:
+    types: [ published ]
+
+jobs:
+  run-ci:
+    uses: ./.github/workflows/ci.yml
+
+  build-sdk:
+    runs-on: ubuntu-latest
+    needs: [ run-ci ]
+    steps:
+      - name: Check out Git repository
+        uses: actions/checkout@v4
+
+      # If you wanted to use multiple Python versions, you'd have specify a matrix in the job and
+      # reference the matrixe python version here.
+      - uses: actions/setup-python@v4
+        with:
+          python-version: "3.11"
+
+      # Cache the installation of Poetry itself, e.g. the next step. This prevents the workflow
+      # from installing Poetry every time, which can be slow. Note the use of the Poetry version
+      # number in the cache key, and the "-0" suffix: this allows you to invalidate the cache
+      # manually if/when you want to upgrade Poetry, or if something goes wrong. This could be
+      # mildly cleaner by using an environment variable, but I don't really care.
+      - name: cache poetry install
+        uses: actions/cache@v3
+        with:
+          path: ~/.local
+          key: poetry-1.7.1
+
+      # Install Poetry. You could do this manually, or there are several actions that do this.
+      # `snok/install-poetry` seems to be minimal yet complete, and really just calls out to
+      # Poetry's default install script, which feels correct. I pin the Poetry version here
+      # because Poetry does occasionally change APIs between versions and I don't want my
+      # actions to break if it does.
+      #
+      # The key configuration value here is `virtualenvs-in-project: true`: this creates the
+      # venv as a `.venv` in your testing directory, which allows the next step to easily
+      # cache it.
+      - uses: snok/install-poetry@v1
+        with:
+          version: 1.7.1
+          virtualenvs-create: true
+          virtualenvs-in-project: true
+
+      # Cache your dependencies (i.e. all the stuff in your `pyproject.toml`). Note the cache
+      # key: if you're using multiple Python versions, or multiple OSes, you'd need to include
+      # them in the cache key. I'm not, so it can be simple and just depend on the poetry.lock.
+      - name: cache deps
+        id: cache-deps
+        uses: actions/cache@v3
+        with:
+          path: .venv
+          key: pydeps-${{ hashFiles('**/poetry.lock') }}
+
+      # Install dependencies. `--no-root` means "install all dependencies but not the project
+      # itself", which is what you want to avoid caching _your_ code. The `if` statement
+      # ensures this only runs on a cache miss.
+      - run: poetry install --no-interaction --no-root
+        if: steps.cache-deps.outputs.cache-hit != 'true'
+
+      # Now install _your_ project. This isn't necessary for many types of projects -- particularly
+      # things like Django apps don't need this. But it's a good idea since it fully-exercises the
+      # pyproject.toml and makes that if you add things like console-scripts at some point that
+      # they'll be installed and working.
+      - run: poetry install --no-interaction
+
+      - name: Build Package
+        run: poetry build
+
+      - name: Publish to PyPI
+        env:
+          TWINE_USERNAME: __token__
+          TWINE_PASSWORD: ${{ secrets.PYPI_TOKEN }}
+        run: twine upload --repository pypi dist/*
+
+
+
diff --git a/pyproject.toml b/pyproject.toml
index 7985961d..9f288248 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "skyvern"
-version = "0.1.56"
+version = "0.1.62"
 description = ""
 authors = ["Skyvern AI <info@skyvern.com>"]
 readme = "README.md"