diff --git a/numalogic/backtest/_prom.py b/numalogic/backtest/_prom.py
index 9fc044c7..919d19e7 100644
--- a/numalogic/backtest/_prom.py
+++ b/numalogic/backtest/_prom.py
@@ -30,7 +30,9 @@
     PreprocessFactory,
     PostprocessFactory,
     ThresholdFactory,
+    AggregatorConf,
 )
+from numalogic.config._config import AggMethod
 from numalogic.connectors import ConnectorType
 from numalogic.connectors.prometheus import PrometheusFetcher
 from numalogic.tools.data import StreamingDataset, inverse_window
@@ -238,6 +240,8 @@ def generate_scores(
 
         x_recon = np.zeros((len(ds), self.seq_len, n_feat), dtype=np.float32)
         raw_scores = np.zeros((len(ds), self.seq_len, n_feat), dtype=np.float32)
+        unified_raw_scores = np.zeros((len(ds), 1), dtype=np.float32)
+
         feature_scores = np.zeros((len(ds), n_feat), dtype=np.float32)
         unified_scores = np.zeros((len(ds), 1), dtype=np.float32)
 
@@ -253,12 +257,17 @@ def generate_scores(
 
             winscores = postproc_udf.compute_feature_scores(
                 raw_scores[idx], self.nlconf.score.window_agg
+            )  # (nfeat,)
+
+            unified_raw_scores[idx] = postproc_udf.compute_unified_score(
+                winscores,
+                AggregatorConf(method=AggMethod.MEAN),
             )
 
             feature_scores[idx] = postproc_udf.compute_postprocess(postproc_func, winscores)
 
-            unified_scores[idx] = postproc_udf.compute_unified_score(
-                feature_scores[idx], self.nlconf.score.feature_agg
+            unified_scores[idx] = postproc_udf.compute_postprocess(
+                postproc_func, unified_raw_scores[idx]
             )
 
         x_recon = self.window_inverse(x_recon)
diff --git a/numalogic/config/factory.py b/numalogic/config/factory.py
index a0105329..be2e0777 100644
--- a/numalogic/config/factory.py
+++ b/numalogic/config/factory.py
@@ -51,6 +51,7 @@ class PreprocessFactory(_ObjectFactory):
         GaussianNoiseAdder,
         DifferenceTransform,
         FlattenVector,
+        PercentileScaler,
     )
 
     _CLS_MAP: ClassVar[dict] = {
@@ -65,6 +66,7 @@ class PreprocessFactory(_ObjectFactory):
         "GaussianNoiseAdder": GaussianNoiseAdder,
         "DifferenceTransform": DifferenceTransform,
         "FlattenVector": FlattenVector,
+        "PercentileScaler": PercentileScaler,
     }
 
     def get_pipeline_instance(self, objs_info: list[ModelInfo]):
diff --git a/numalogic/transforms/__init__.py b/numalogic/transforms/__init__.py
index 55186b83..38d2e11f 100644
--- a/numalogic/transforms/__init__.py
+++ b/numalogic/transforms/__init__.py
@@ -14,7 +14,7 @@
 feature engineering and postprocessing.
 """
 
-from numalogic.transforms._scaler import TanhScaler
+from numalogic.transforms._scaler import TanhScaler, PercentileScaler
 from numalogic.transforms._stateless import (
     LogTransformer,
     StaticPowerTransformer,
@@ -38,4 +38,5 @@
     "GaussianNoiseAdder",
     "DifferenceTransform",
     "FlattenVector",
+    "PercentileScaler",
 ]
diff --git a/numalogic/transforms/_scaler.py b/numalogic/transforms/_scaler.py
index 39c59031..4cb7ed2d 100644
--- a/numalogic/transforms/_scaler.py
+++ b/numalogic/transforms/_scaler.py
@@ -11,12 +11,15 @@
 
 
 import logging
+from typing import Optional
 
 import numpy as np
 import numpy.typing as npt
+from sklearn.preprocessing import MinMaxScaler
 from typing_extensions import Self
 
 from numalogic.base import BaseTransformer
+from numalogic.transforms._stateless import DataClipper
 
 LOGGER = logging.getLogger(__name__)
 
@@ -69,3 +72,39 @@ def fit_transform(self, x: npt.NDArray[float], y=None, **_) -> npt.NDArray[float
     def _check_if_constant(self, x: npt.NDArray[float]) -> None:
         delta = np.max(x, axis=0) - np.min(x, axis=0)
         self._std[delta < self._eps] = 1.0
+
+
+class PercentileScaler(BaseTransformer):
+    """
+    Scales the data based on the percentiles of the data.
+
+    Args:
+    -----
+        max_percentile: float, optional
+            The upper percentile to clip the data.
+            Default is 90.
+        min_percentile: float, optional
+            The lower percentile to clip the data.
+            If None, minimum value of the data is used.
+            Default is None.
+    """
+
+    def __init__(self, max_percentile: float = 95, min_percentile: Optional[float] = None):
+        self._max_px = max_percentile
+        self._min_px = min_percentile
+        self.tx = MinMaxScaler()
+
+    def fit(self, x: npt.NDArray[float]) -> Self:
+        data_max_px = np.percentile(x, self._max_px, axis=0)
+        if self._min_px is None:
+            data_min_px = np.min(x, axis=0)
+        else:
+            data_min_px = np.percentile(x, self._min_px, axis=0)
+        x_clipped = DataClipper(lower=data_min_px, upper=data_max_px).transform(x)
+        return self.tx.fit(x_clipped)
+
+    def fit_transform(self, x: npt.NDArray[float], y=None, **_):
+        return self.fit(x).transform(x)
+
+    def transform(self, x: npt.NDArray[float]) -> npt.NDArray[float]:
+        return self.tx.transform(x)
diff --git a/numalogic/udfs/postprocess.py b/numalogic/udfs/postprocess.py
index 36af8195..d9a6aa5c 100644
--- a/numalogic/udfs/postprocess.py
+++ b/numalogic/udfs/postprocess.py
@@ -139,19 +139,14 @@ def exec(self, keys: list[str], datum: Datum) -> Messages:
 
         #  Postprocess payload
         try:
-            # Compute anomaly scores per feature
-            a_features = self.compute(
+            # Compute anomaly scores
+            a_unified, a_features = self.compute(
                 model=thresh_artifact.artifact,
                 input_=payload.get_data(),
                 score_conf=_conf.numalogic_conf.score,
                 postproc_tx=postproc_tx,
             )  # (nfeat,)
 
-            # Compute unified score
-            a_unified = self.compute_unified_score(
-                a_features, feat_agg_conf=_conf.numalogic_conf.score.feature_agg
-            )
-
             # Calculate adjusted unified score
             a_adjusted, y_unified, y_features = self._adjust_score(_conf, a_unified, payload)
 
@@ -302,7 +297,7 @@ def compute(
         postproc_tx=None,
         score_conf: Optional[ScoreConf] = None,
         **_,
-    ) -> NDArray[float]:
+    ) -> tuple[float, NDArray[float]]:
         """
         Compute thresholding, window aggregation followed by postprocess.
 
@@ -315,7 +310,7 @@ def compute(
 
         Returns
         -------
-        Output data of shape (n_features, )
+        Tuple of combined/unified score (float), and feature scores of shape (n_features,)
 
         Raises
         ------
@@ -325,13 +320,23 @@ def compute(
             _struct_log.warning("Score config not provided, using default values")
             score_conf = ScoreConf()
 
-        scores = cls.compute_threshold(model, input_)  # (seqlen x nfeat)
-        win_scores = cls.compute_feature_scores(
-            scores, win_agg_conf=score_conf.window_agg
+        thresh_scores = cls.compute_threshold(model, input_)  # (seqlen x nfeat)
+
+        # Aggregate over the sequence length
+        raw_scores = cls.compute_feature_scores(
+            thresh_scores, win_agg_conf=score_conf.window_agg
         )  # (nfeat,)
+
+        # Aggregate over the features
+        unified_raw_score = cls.compute_unified_score(raw_scores, score_conf.feature_agg)  # float
+
         if postproc_tx:
-            win_scores = cls.compute_postprocess(postproc_tx, win_scores)  # (nfeat,)
-        return win_scores  # (nfeat, )
+            # Postprocess the raw scores
+            feature_scores = cls.compute_postprocess(postproc_tx, raw_scores)  # (nfeat,)
+            unified_score = cls.compute_postprocess(postproc_tx, unified_raw_score)  # float
+            return unified_score, feature_scores
+
+        return unified_raw_score, raw_scores
 
     @classmethod
     def compute_threshold(cls, model: artifact_t, input_: NDArray[float]) -> NDArray[float]:
diff --git a/poetry.lock b/poetry.lock
index 96046ef9..9addda54 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -1,89 +1,88 @@
 # This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand.
 
-
 [[package]]
 name = "aiohttp"
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+version = "3.9.5"
 description = "Async http client/server framework (asyncio)"
 optional = false
 python-versions = ">=3.8"
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 ]
 
 [package.dependencies]
@@ -407,17 +406,17 @@ css = ["tinycss2 (>=1.1.0,<1.3)"]
 
 [[package]]
 name = "boto3"
-version = "1.34.80"
+version = "1.34.87"
 description = "The AWS SDK for Python"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
-botocore = ">=1.34.80,<1.35.0"
+botocore = ">=1.34.87,<1.35.0"
 jmespath = ">=0.7.1,<2.0.0"
 s3transfer = ">=0.10.0,<0.11.0"
 
@@ -426,13 +425,13 @@ crt = ["botocore[crt] (>=1.21.0,<2.0a0)"]
 
 [[package]]
 name = "botocore"
-version = "1.34.80"
+version = "1.34.87"
 description = "Low-level, data-driven core of boto 3."
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -444,7 +443,7 @@ urllib3 = [
 ]
 
 [package.extras]
-crt = ["awscrt (==0.19.19)"]
+crt = ["awscrt (==0.20.9)"]
 
 [[package]]
 name = "bottleneck"
@@ -1047,13 +1046,13 @@ files = [
 
 [[package]]
 name = "exceptiongroup"
-version = "1.2.0"
+version = "1.2.1"
 description = "Backport of PEP 654 (exception groups)"
 optional = false
 python-versions = ">=3.7"
 files = [
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 ]
 
 [package.extras]
@@ -1111,13 +1110,13 @@ devel = ["colorama", "json-spec", "jsonschema", "pylint", "pytest", "pytest-benc
 
 [[package]]
 name = "filelock"
-version = "3.13.3"
+version = "3.13.4"
 description = "A platform independent file lock."
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 python-versions = ">=3.8"
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 [package.extras]
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 [package.extras]
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 optional = false
 python-versions = ">=3.7"
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 ]
 
 [package.dependencies]
-grpcio = ">=1.62.1"
+grpcio = ">=1.62.2"
 protobuf = ">=4.21.6,<5.0dev"
 setuptools = "*"
 
@@ -1840,13 +1768,13 @@ license = ["ukkonen"]
 
 [[package]]
 name = "idna"
-version = "3.6"
+version = "3.7"
 description = "Internationalized Domain Names in Applications (IDNA)"
 optional = false
 python-versions = ">=3.5"
 files = [
-    {file = "idna-3.6-py3-none-any.whl", hash = "sha256:c05567e9c24a6b9faaa835c4821bad0590fbb9d5779e7caa6e1cc4978e7eb24f"},
-    {file = "idna-3.6.tar.gz", hash = "sha256:9ecdbbd083b06798ae1e86adcbfe8ab1479cf864e4ee30fe4e46a003d12491ca"},
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 ]
 
 [[package]]
@@ -1932,13 +1860,13 @@ test = ["flaky", "ipyparallel", "pre-commit", "pytest (>=7.0)", "pytest-asyncio
 
 [[package]]
 name = "ipympl"
-version = "0.9.3"
+version = "0.9.4"
 description = "Matplotlib Jupyter Extension"
 optional = false
-python-versions = "*"
+python-versions = ">=3.9"
 files = [
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 ]
 
 [package.dependencies]
@@ -1951,7 +1879,7 @@ pillow = "*"
 traitlets = "<6"
 
 [package.extras]
-docs = ["Sphinx (>=1.5)", "myst-nb", "sphinx-book-theme", "sphinx-copybutton", "sphinx-thebe", "sphinx-togglebutton"]
+docs = ["myst-nb", "sphinx (>=1.5)", "sphinx-book-theme", "sphinx-copybutton", "sphinx-thebe", "sphinx-togglebutton"]
 
 [[package]]
 name = "ipython"
@@ -2110,13 +2038,13 @@ files = [
 
 [[package]]
 name = "json5"
-version = "0.9.24"
+version = "0.9.25"
 description = "A Python implementation of the JSON5 data format."
 optional = false
 python-versions = ">=3.8"
 files = [
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+    {file = "json5-0.9.25.tar.gz", hash = "sha256:548e41b9be043f9426776f05df8635a00fe06104ea51ed24b67f908856e151ae"},
 ]
 
 [[package]]
@@ -2287,13 +2215,13 @@ test = ["click", "pre-commit", "pytest (>=7.0)", "pytest-asyncio (>=0.19.0)", "p
 
 [[package]]
 name = "jupyter-lsp"
-version = "2.2.4"
+version = "2.2.5"
 description = "Multi-Language Server WebSocket proxy for Jupyter Notebook/Lab server"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -2302,39 +2230,39 @@ jupyter-server = ">=1.1.2"
 
 [[package]]
 name = "jupyter-server"
-version = "2.13.0"
+version = "2.14.0"
 description = "The backend—i.e. core services, APIs, and REST endpoints—to Jupyter web applications."
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
 anyio = ">=3.1.0"
-argon2-cffi = "*"
-jinja2 = "*"
+argon2-cffi = ">=21.1"
+jinja2 = ">=3.0.3"
 jupyter-client = ">=7.4.4"
 jupyter-core = ">=4.12,<5.0.dev0 || >=5.1.dev0"
 jupyter-events = ">=0.9.0"
-jupyter-server-terminals = "*"
+jupyter-server-terminals = ">=0.4.4"
 nbconvert = ">=6.4.4"
 nbformat = ">=5.3.0"
-overrides = "*"
-packaging = "*"
-prometheus-client = "*"
-pywinpty = {version = "*", markers = "os_name == \"nt\""}
+overrides = ">=5.0"
+packaging = ">=22.0"
+prometheus-client = ">=0.9"
+pywinpty = {version = ">=2.0.1", markers = "os_name == \"nt\""}
 pyzmq = ">=24"
 send2trash = ">=1.8.2"
 terminado = ">=0.8.3"
 tornado = ">=6.2.0"
 traitlets = ">=5.6.0"
-websocket-client = "*"
+websocket-client = ">=1.7"
 
 [package.extras]
 docs = ["ipykernel", "jinja2", "jupyter-client", "jupyter-server", "myst-parser", "nbformat", "prometheus-client", "pydata-sphinx-theme", "send2trash", "sphinx-autodoc-typehints", "sphinxcontrib-github-alt", "sphinxcontrib-openapi (>=0.8.0)", "sphinxcontrib-spelling", "sphinxemoji", "tornado", "typing-extensions"]
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+test = ["flaky", "ipykernel", "pre-commit", "pytest (>=7.0,<9)", "pytest-console-scripts", "pytest-jupyter[server] (>=0.7)", "pytest-timeout", "requests"]
 
 [[package]]
 name = "jupyter-server-terminals"
@@ -2721,13 +2649,13 @@ python-dateutil = ">=2.7"
 
 [[package]]
 name = "matplotlib-inline"
-version = "0.1.6"
+version = "0.1.7"
 description = "Inline Matplotlib backend for Jupyter"
 optional = false
-python-versions = ">=3.5"
+python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -2746,13 +2674,13 @@ files = [
 
 [[package]]
 name = "mlflow-skinny"
-version = "2.11.3"
-description = "MLflow: A Platform for ML Development and Productionization"
+version = "2.12.1"
+description = "MLflow is an open source platform for the complete machine learning lifecycle"
 optional = true
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -2761,8 +2689,8 @@ cloudpickle = "<4"
 entrypoints = "<1"
 gitpython = ">=3.1.9,<4"
 importlib-metadata = ">=3.7.0,<4.7.0 || >4.7.0,<8"
-packaging = "<24"
-protobuf = ">=3.12.0,<5"
+packaging = "<25"
+protobuf = ">=3.12.0,<6"
 pytz = "<2025"
 pyyaml = ">=5.1,<7"
 requests = ">=2.17.3,<3"
@@ -3078,13 +3006,13 @@ setuptools = "*"
 
 [[package]]
 name = "notebook"
-version = "7.1.2"
+version = "7.1.3"
 description = "Jupyter Notebook - A web-based notebook environment for interactive computing"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -3408,62 +3336,62 @@ dev = ["black", "mypy", "pytest"]
 
 [[package]]
 name = "orjson"
-version = "3.10.0"
+version = "3.10.1"
 description = "Fast, correct Python JSON library supporting dataclasses, datetimes, and numpy"
 optional = false
 python-versions = ">=3.8"
 files = [
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 threadpoolctl = ">=2.0.0"
 
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-    {file = "SQLAlchemy-2.0.29-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:25664e18bef6dc45015b08f99c63952a53a0a61f61f2e48a9e70cec27e55f699"},
-    {file = "SQLAlchemy-2.0.29-cp39-cp39-win32.whl", hash = "sha256:77d29cb6c34b14af8a484e831ab530c0f7188f8efed1c6a833a2c674bf3c26ec"},
-    {file = "SQLAlchemy-2.0.29-cp39-cp39-win_amd64.whl", hash = "sha256:04c487305ab035a9548f573763915189fc0fe0824d9ba28433196f8436f1449c"},
-    {file = "SQLAlchemy-2.0.29-py3-none-any.whl", hash = "sha256:dc4ee2d4ee43251905f88637d5281a8d52e916a021384ec10758826f5cbae305"},
-    {file = "SQLAlchemy-2.0.29.tar.gz", hash = "sha256:bd9566b8e58cabd700bc367b60e90d9349cd16f0984973f98a9a09f9c64e86f0"},
-]
-
-[package.dependencies]
-greenlet = {version = "!=0.4.17", markers = "platform_machine == \"aarch64\" or platform_machine == \"ppc64le\" or platform_machine == \"x86_64\" or platform_machine == \"amd64\" or platform_machine == \"AMD64\" or platform_machine == \"win32\" or platform_machine == \"WIN32\""}
-typing-extensions = ">=4.6.0"
-
-[package.extras]
-aiomysql = ["aiomysql (>=0.2.0)", "greenlet (!=0.4.17)"]
-aioodbc = ["aioodbc", "greenlet (!=0.4.17)"]
-aiosqlite = ["aiosqlite", "greenlet (!=0.4.17)", "typing_extensions (!=3.10.0.1)"]
-asyncio = ["greenlet (!=0.4.17)"]
-asyncmy = ["asyncmy (>=0.2.3,!=0.2.4,!=0.2.6)", "greenlet (!=0.4.17)"]
-mariadb-connector = ["mariadb (>=1.0.1,!=1.1.2,!=1.1.5)"]
-mssql = ["pyodbc"]
-mssql-pymssql = ["pymssql"]
-mssql-pyodbc = ["pyodbc"]
-mypy = ["mypy (>=0.910)"]
-mysql = ["mysqlclient (>=1.4.0)"]
-mysql-connector = ["mysql-connector-python"]
-oracle = ["cx_oracle (>=8)"]
-oracle-oracledb = ["oracledb (>=1.0.1)"]
-postgresql = ["psycopg2 (>=2.7)"]
-postgresql-asyncpg = ["asyncpg", "greenlet (!=0.4.17)"]
-postgresql-pg8000 = ["pg8000 (>=1.29.1)"]
-postgresql-psycopg = ["psycopg (>=3.0.7)"]
-postgresql-psycopg2binary = ["psycopg2-binary"]
-postgresql-psycopg2cffi = ["psycopg2cffi"]
-postgresql-psycopgbinary = ["psycopg[binary] (>=3.0.7)"]
-pymysql = ["pymysql"]
-sqlcipher = ["sqlcipher3_binary"]
-
 [[package]]
 name = "sqlparse"
-version = "0.4.4"
+version = "0.5.0"
 description = "A non-validating SQL parser."
 optional = true
-python-versions = ">=3.5"
+python-versions = ">=3.8"
 files = [
-    {file = "sqlparse-0.4.4-py3-none-any.whl", hash = "sha256:5430a4fe2ac7d0f93e66f1efc6e1338a41884b7ddf2a350cedd20ccc4d9d28f3"},
-    {file = "sqlparse-0.4.4.tar.gz", hash = "sha256:d446183e84b8349fa3061f0fe7f06ca94ba65b426946ffebe6e3e8295332420c"},
+    {file = "sqlparse-0.5.0-py3-none-any.whl", hash = "sha256:c204494cd97479d0e39f28c93d46c0b2d5959c7b9ab904762ea6c7af211c8663"},
+    {file = "sqlparse-0.5.0.tar.gz", hash = "sha256:714d0a4932c059d16189f58ef5411ec2287a4360f17cdd0edd2d09d4c5087c93"},
 ]
 
 [package.extras]
-dev = ["build", "flake8"]
+dev = ["build", "hatch"]
 doc = ["sphinx"]
-test = ["pytest", "pytest-cov"]
 
 [[package]]
 name = "stack-data"
@@ -5270,13 +5105,13 @@ zstd = ["zstandard (>=0.18.0)"]
 
 [[package]]
 name = "virtualenv"
-version = "20.25.1"
+version = "20.25.3"
 description = "Virtual Python Environment builder"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "virtualenv-20.25.1-py3-none-any.whl", hash = "sha256:961c026ac520bac5f69acb8ea063e8a4f071bcc9457b9c1f28f6b085c511583a"},
-    {file = "virtualenv-20.25.1.tar.gz", hash = "sha256:e08e13ecdca7a0bd53798f356d5831434afa5b07b93f0abdf0797b7a06ffe197"},
+    {file = "virtualenv-20.25.3-py3-none-any.whl", hash = "sha256:8aac4332f2ea6ef519c648d0bc48a5b1d324994753519919bddbb1aff25a104e"},
+    {file = "virtualenv-20.25.3.tar.gz", hash = "sha256:7bb554bbdfeaacc3349fa614ea5bff6ac300fc7c335e9facf3a3bcfc703f45be"},
 ]
 
 [package.dependencies]
@@ -5285,7 +5120,7 @@ filelock = ">=3.12.2,<4"
 platformdirs = ">=3.9.1,<5"
 
 [package.extras]
-docs = ["furo (>=2023.7.26)", "proselint (>=0.13)", "sphinx (>=7.1.2)", "sphinx-argparse (>=0.4)", "sphinxcontrib-towncrier (>=0.2.1a0)", "towncrier (>=23.6)"]
+docs = ["furo (>=2023.7.26)", "proselint (>=0.13)", "sphinx (>=7.1.2,!=7.3)", "sphinx-argparse (>=0.4)", "sphinxcontrib-towncrier (>=0.2.1a0)", "towncrier (>=23.6)"]
 test = ["covdefaults (>=2.3)", "coverage (>=7.2.7)", "coverage-enable-subprocess (>=1)", "flaky (>=3.7)", "packaging (>=23.1)", "pytest (>=7.4)", "pytest-env (>=0.8.2)", "pytest-freezer (>=0.4.8)", "pytest-mock (>=3.11.1)", "pytest-randomly (>=3.12)", "pytest-timeout (>=2.1)", "setuptools (>=68)", "time-machine (>=2.10)"]
 
 [[package]]
@@ -5499,14 +5334,13 @@ docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.link
 testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "pytest (>=6)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-ignore-flaky", "pytest-mypy", "pytest-ruff (>=0.2.1)"]
 
 [extras]
-boto3 = ["boto3"]
 druid = ["pydruid"]
 dynamodb = ["boto3"]
 mlflow = ["mlflow-skinny"]
-rds = ["PyMySQL", "boto3", "cryptography"]
+rds = ["PyMySQL", "boto3"]
 redis = ["redis"]
 
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.9, <3.12"
-content-hash = "1778c3a607e9576b230ab76507c4914d54d46d91f30c8f887bb8b6ec2f2d3191"
+content-hash = "dda939314986db31121d74b38f9ebb0b73da1a66badb6177e692cf52065987b6"
diff --git a/pyproject.toml b/pyproject.toml
index 30bf4f4f..59c1ce8d 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -33,14 +33,12 @@ cachetools = "^5.3.0"
 orjson = "^3.9"
 pynumaflow = "~0.6"
 prometheus_client = "^0.18.0"
+structlog = "^24.1.0"
 
 # extras
 mlflow-skinny = { version = "^2.0", optional = true }
 redis = { extras = ["hiredis"], version = "^5.0", optional = true }
 boto3 = { version = "^1.24.64", optional = true }
-
-structlog = "^24.1.0"
-
 pydruid = { version = "^0.6", optional = true }
 PyMySQL = { version = "^1.1.0", optional = true }
 
diff --git a/tests/udfs/test_postprocess.py b/tests/udfs/test_postprocess.py
index 4101eece..e6979f12 100644
--- a/tests/udfs/test_postprocess.py
+++ b/tests/udfs/test_postprocess.py
@@ -173,5 +173,6 @@ def test_postprocess_runtime_err_02(udf, mocker, bad_artifact):
 
 
 def test_compute(udf, artifact):
-    x_inferred = udf.compute(artifact.artifact, np.asarray(DATA["data"]))
+    y_unified, x_inferred = udf.compute(artifact.artifact, np.asarray(DATA["data"]))
+    assert isinstance(y_unified, float)
     assert x_inferred.shape == (2,)