diff --git a/otava/change_point_divisive/base.py b/otava/change_point_divisive/base.py
index d5e0eb20..b2a088e3 100644
--- a/otava/change_point_divisive/base.py
+++ b/otava/change_point_divisive/base.py
@@ -201,9 +201,8 @@ def to_candidate(self) -> CandidateChangePoint:
         data = {f.name: getattr(self, f.name) for f in fields(CandidateChangePoint)}
         return CandidateChangePoint(**data)
 
-    def to_json(self, rounded=True):
-        cps = ChangePointSerializer(self)
-        return cps.to_json(rounded)
+    def to_json(self):
+        return ChangePointSerializer(self).to_json()
 
 
 class ChangePointSerializer(ChangePoint):
@@ -217,6 +216,7 @@ class ChangePointSerializer(ChangePoint):
     def __init__(self, cp: ChangePoint[GenericStats]):
         self.stats = cp.stats
         self.index = cp.index
+        self.qhat = cp.qhat
         self.metric = cp.metric
 
     def forward_change_percent(self) -> float:
@@ -243,33 +243,19 @@ def stddev_after(self):
     def pvalue(self):
         return self.stats.pvalue
 
-    def to_json(self, rounded=True):
-        if rounded:
-            return {
-                "metric": self.metric,
-                "index": int(self.index),
-                "forward_change_percent": f"{self.forward_change_percent():.0f}",
-                "backward_change_percent": f"{self.backward_change_percent():.0f}",
-                "magnitude": f"{self.magnitude():-0f}",
-                "mean_before": f"{self.mean_before():-0f}",
-                "stddev_before": f"{self.stddev_before():-0f}",
-                "mean_after": f"{self.mean_after():-0f}",
-                "stddev_after": f"{self.stddev_after():-0f}",
-                "pvalue": f"{self.pvalue():-0f}",
-            }
-
-        else:
-            return {
-                "metric": self.metric,
-                "index": int(self.index),
-                "forward_change_percent": self.forward_change_percent(),
-                "magnitude": self.magnitude(),
-                "mean_before": self.mean_before(),
-                "stddev_before": self.stddev_before(),
-                "mean_after": self.mean_after(),
-                "stddev_after": self.stddev_after(),
-                "pvalue": self.pvalue(),
-            }
+    def to_json(self):
+        return {
+            "metric": self.metric,
+            "index": int(self.index),
+            "qhat": self.qhat,
+            "forward_change_percent": self.forward_change_percent(),
+            "magnitude": self.magnitude(),
+            "mean_before": self.mean_before(),
+            "stddev_before": self.stddev_before(),
+            "mean_after": self.mean_after(),
+            "stddev_after": self.stddev_after(),
+            "pvalue": self.pvalue(),
+        }
 
 
 @dataclass
@@ -288,15 +274,16 @@ class ChangePointGroup:
     :param attributes: The attributes of the test result at this timestamp. Commit and test metadata.
     :param changes: For each metric that has a change point at this time(stamp), the ChangePoint object.
     """
+
     time: float
     attributes: Dict[str, str]
     # ChangePointGroup.changes.keys() stores the set of metrics that were used at this ChangePointGroup.time.
     changes: Dict[str, ChangePoint]
 
-    def to_json(self, rounded=False):
+    def to_json(self):
         changes = []
         for metric, cp in self.changes.items():
-            changes.append(cp.to_json(rounded=rounded))
+            changes.append(cp.to_json())
 
         return {
             "time": self.time,
@@ -365,9 +352,7 @@ def __init__(self):
     def from_list(cls, cps: list[ChangePointGroup]):
         """Build from a list of ChangePointGroup objects, ordered by time."""
         if not isinstance(cps, list):
-            raise TypeError(
-                f"from_list() argument must be a list. Got {type(cps)}."
-            )
+            raise TypeError(f"from_list() argument must be a list. Got {type(cps)}.")
         for cpg in cps:
             if not isinstance(cpg, ChangePointGroup):
                 raise TypeError(
@@ -396,12 +381,12 @@ def from_dict(cls, cps: dict):
         for metric, cpglist in cps.items():
             for cpg in cpglist:
                 if not isinstance(cpg, ChangePointGroup):
-                    raise TypeError(
-                        "from_dict() takes a dict[str, list[ChangePointGroup]]."
-                    )
+                    raise TypeError("from_dict() takes a dict[str, list[ChangePointGroup]].")
                 for cp in cpg:
                     if cp.metric and cp.metric != metric:
-                        raise ValueError(f"metric field is not internally consistent. {cp.metric} != {metric} at {cpg.time}")
+                        raise ValueError(
+                            f"metric field is not internally consistent. {cp.metric} != {metric} at {cpg.time}"
+                        )
             # store each metric's groups sorted by timestamp
             obj._change_points[metric] = sorted(cpglist, key=lambda cpg: cpg.time)
         return obj
@@ -522,7 +507,9 @@ def get_change_points_for_metric(self, m: str):
         for cpg in single_metric._change_points:
             for metric, cp in cpg.changes.items():
                 if cp.metric and cp.metric != metric:
-                    raise ValueError(f"metric field is not internally consistent. {cp.metric} != {metric} at {cpg.time}")
+                    raise ValueError(
+                        f"metric field is not internally consistent. {cp.metric} != {metric} at {cpg.time}"
+                    )
                 metric_change_points.append(cp)
         return metric_change_points
 
@@ -536,7 +523,7 @@ def at_timestamp(self, t: float):
 
     def at_commit(self, sha: str):
         for row in self:
-            if row.attributes['commit'] == sha:
+            if row.attributes["commit"] == sha:
                 return row
         raise LookupError(sha)
 
@@ -555,17 +542,18 @@ def pivot(self):
 
 class ChangePointsByTime(ChangePoints):
     """
-        Implementation of ChangePoints class where the internal structure is ordered by time/commit.
+    Implementation of ChangePoints class where the internal structure is ordered by time/commit.
 
-        In fact, this is the default way, and therefore all of this class' implementation is already
-        in its parent class ChangePoints. However, you can still create instances from this class
-        to make it explicit that your code at that point explicitly wanted a collection of ChangePoints
-        ordered by time.
+    In fact, this is the default way, and therefore all of this class' implementation is already
+    in its parent class ChangePoints. However, you can still create instances from this class
+    to make it explicit that your code at that point explicitly wanted a collection of ChangePoints
+    ordered by time.
 
-        The pivot() method returns a new view holding the same ChangePoint objects, but ordered by metrics
-        as the primary and optimized axis. The method by_metric() can be used for the same purpose. Use
-        copy().pivot() for an isolated copy. The method by_time() is a no-op and returns self.
+    The pivot() method returns a new view holding the same ChangePoint objects, but ordered by metrics
+    as the primary and optimized axis. The method by_metric() can be used for the same purpose. Use
+    copy().pivot() for an isolated copy. The method by_time() is a no-op and returns self.
     """
+
     @classmethod
     def from_dict(cls, cps: dict):
         """
@@ -579,14 +567,14 @@ def from_dict(cls, cps: dict):
 
 class ChangePointsByMetric(ChangePoints):
     """
-        Provides same interface as ChangePointsByTime, but internally stores with metric first.
+    Provides same interface as ChangePointsByTime, but internally stores with metric first.
 
-        You can create empty instances of this class, or you can also use the factory method
-        `ChangePoints.from_dict()` to get an instance of this type.
+    You can create empty instances of this class, or you can also use the factory method
+    `ChangePoints.from_dict()` to get an instance of this type.
 
-        The pivot() method returns a new view holding the same ChangePoint objects, but ordered by time
-        as the primary and optimized axis. The method by_time() can be used for the same purpose. Use
-        copy().pivot() for an isolated copy. The method by_metric() is a no-op and returns self.
+    The pivot() method returns a new view holding the same ChangePoint objects, but ordered by time
+    as the primary and optimized axis. The method by_time() can be used for the same purpose. Use
+    copy().pivot() for an isolated copy. The method by_metric() is a no-op and returns self.
     """
 
     def __init__(self):
@@ -636,7 +624,9 @@ def append(self, cpg: ChangePointGroup):
                 self._change_points[metric] = []
             for metric1, cp in cpg.changes.items():
                 if metric1 != cp.metric:
-                    raise ValueError(f"metric field is not internally consistent. {metric1} != {cp.metric} at {cpg.time}")
+                    raise ValueError(
+                        f"metric field is not internally consistent. {metric1} != {cp.metric} at {cpg.time}"
+                    )
             if (not self._change_points[metric]) or cpg.time > self._change_points[metric][-1].time:
                 self._change_points[metric].append(cpg.select_metrics(metric))
             else:
@@ -653,10 +643,14 @@ def extend(self, cps: list[ChangePointGroup]):
                 raise TypeError(errmsg)
             for metric1, cp in cpg.changes.items():
                 if metric1 != cp.metric:
-                    raise ValueError(f"metric field is not internally consistent. {metric1} != {cp.metric} at {cpg.time}")
+                    raise ValueError(
+                        f"metric field is not internally consistent. {metric1} != {cp.metric} at {cpg.time}"
+                    )
                 if metric1 not in self._change_points:
                     self._change_points[metric1] = []
-                if (not self._change_points[metric1]) or cpg.time > self._change_points[metric1][-1].time:
+                if (not self._change_points[metric1]) or cpg.time > self._change_points[metric1][
+                    -1
+                ].time:
                     self._change_points[metric1].append(cpg.select_metrics(metric1))
                 else:
                     raise ValueError(
@@ -728,7 +722,9 @@ def get_change_points_for_metric(self, m: str):
             for cpg in cpglist:
                 for metric2, cp in cpg.changes.items():
                     if metric1 != metric2 or cp.metric and metric1 != cp.metric:
-                        raise ValueError(f"metric field is not internally consistent. {metric1} != {cp.metric} at {cpg.time}")
+                        raise ValueError(
+                            f"metric field is not internally consistent. {metric1} != {cp.metric} at {cpg.time}"
+                        )
                     metric_change_points.append(cp)
 
         return metric_change_points
@@ -752,13 +748,18 @@ class SignificanceTester(Generic[GenericStats]):
     def __init__(self, max_pvalue: float):
         self.max_pvalue = max_pvalue
 
-    def compare(self, left: Sequence[SupportsFloat], right: Sequence[SupportsFloat], p: float = None) -> GenericStats:
+    def compare(
+        self, left: Sequence[SupportsFloat], right: Sequence[SupportsFloat], p: float = None
+    ) -> GenericStats:
         if len(left) == 0 or len(right) == 0:
             raise ValueError
         return BaseStats.calculate(left, right, p)
 
     def get_sides(
-        self, candidate: CandidateChangePoint, series: Sequence[SupportsFloat], intervals: List[slice]
+        self,
+        candidate: CandidateChangePoint,
+        series: Sequence[SupportsFloat],
+        intervals: List[slice],
     ) -> (Sequence, Sequence):
         """
         Computes properties of the change point if the Candidate Change Point based on the provided intervals.
@@ -779,7 +780,9 @@ def get_sides(
                 left_interval = interval
                 right_interval = intervals[i + 1]
                 break
-            elif (interval.start is None or interval.start < candidate.index) and (interval.stop is None or candidate.index < interval.stop):
+            elif (interval.start is None or interval.start < candidate.index) and (
+                interval.stop is None or candidate.index < interval.stop
+            ):
                 # Split step
                 # Note: handles slices with omitted indexes:
                 #
diff --git a/otava/report.py b/otava/report.py
index 5431b825..1f1e3dc8 100644
--- a/otava/report.py
+++ b/otava/report.py
@@ -103,7 +103,37 @@ def __format_log_annotated(self, test_name: str) -> str:
     def __format_json(self, test_name: str) -> str:
         import json
 
-        return json.dumps({test_name: [cpg.to_json(rounded=True) for cpg in self.__change_points]})
+        return json.dumps(
+            {
+                test_name: [
+                    self.__format_change_point_group_json(cpg) for cpg in self.__change_points
+                ]
+            }
+        )
+
+    @staticmethod
+    def __format_change_point_group_json(cpg):
+        return {
+            "time": cpg.time,
+            "attributes": cpg.attributes,
+            "changes": [Report.__format_change_point_json(cp) for cp in cpg.changes.values()],
+        }
+
+    @staticmethod
+    def __format_change_point_json(cp):
+        cp = ChangePointSerializer(cp)
+        return {
+            "metric": cp.metric,
+            "index": int(cp.index),
+            "forward_change_percent": f"{cp.forward_change_percent():.0f}",
+            "backward_change_percent": f"{cp.backward_change_percent():.0f}",
+            "magnitude": f"{cp.magnitude():.6f}",
+            "mean_before": f"{cp.mean_before():.6f}",
+            "stddev_before": f"{cp.stddev_before():.6f}",
+            "mean_after": f"{cp.mean_after():.6f}",
+            "stddev_after": f"{cp.stddev_after():.6f}",
+            "pvalue": f"{cp.pvalue():.6f}",
+        }
 
     def __format_regressions_only(self, test_name: str) -> str:
         output = []
diff --git a/otava/serialization.py b/otava/serialization.py
new file mode 100644
index 00000000..1b95ad8b
--- /dev/null
+++ b/otava/serialization.py
@@ -0,0 +1,72 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License.  You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied.  See the License for the
+# specific language governing permissions and limitations
+# under the License.
+
+from datetime import datetime
+from typing import Dict, List, Optional
+
+from pydantic import BaseModel, ConfigDict
+
+JsonScalar = str | int | float | bool | None
+
+
+class AnalysisOptionsModel(BaseModel):
+    model_config = ConfigDict(extra="forbid", validate_assignment=True)
+
+    window_len: int = 50
+    max_pvalue: float = 0.001
+    min_magnitude: float = 0.0
+    orig_edivisive: bool = False
+
+
+class MetricModel(BaseModel):
+    direction: Optional[int] = None
+    scale: Optional[float] = None
+    unit: str = ""
+
+
+class ChangePointModel(BaseModel):
+    metric: Optional[str] = None
+    index: int
+    qhat: float
+    forward_change_percent: float
+    magnitude: float
+    mean_before: float
+    stddev_before: float
+    mean_after: float
+    stddev_after: float
+    pvalue: float
+
+
+class ChangePointGroupModel(BaseModel):
+    time: int | float
+    attributes: Dict[str, JsonScalar]
+    changes: List[ChangePointModel]
+
+
+class AnalyzedSeriesModel(BaseModel):
+    model_config = ConfigDict(arbitrary_types_allowed=False)
+
+    test_name: str
+    time: List[int | float]
+    change_points_timestamp: datetime
+    branch_name: Optional[str] = None
+    options: AnalysisOptionsModel
+    metrics: Dict[str, MetricModel]
+    attributes: Dict[str, List[JsonScalar]]
+    data: Dict[str, List[Optional[float]]]
+    change_points: Dict[str, List[ChangePointGroupModel]]
+    weak_change_points: Dict[str, List[ChangePointGroupModel]]
diff --git a/otava/series.py b/otava/series.py
index e3d9e828..cb10d7b5 100644
--- a/otava/series.py
+++ b/otava/series.py
@@ -20,6 +20,8 @@
 from datetime import datetime, timezone
 from typing import Dict, Iterable, List, Optional
 
+from pydantic import TypeAdapter
+
 from otava.analysis import (
     TTestStats,
     compute_change_points,
@@ -32,28 +34,13 @@
     ChangePointsByMetric,
     ChangePointsByTime,
 )
+from otava.serialization import AnalysisOptionsModel, AnalyzedSeriesModel, JsonScalar
 
+_datetime_adapter = TypeAdapter(datetime)
 
-@dataclass
-class AnalysisOptions:
-    window_len: int
-    max_pvalue: float
-    min_magnitude: float
-    orig_edivisive: bool
-
-    def __init__(self):
-        self.window_len = 50
-        self.max_pvalue = 0.001
-        self.min_magnitude = 0.0
-        self.orig_edivisive = False
 
-    def to_json(self):
-        return {
-            "window_len": self.window_len,
-            "max_pvalue": self.max_pvalue,
-            "min_magnitude": self.min_magnitude,
-            "orig_edivisive": self.orig_edivisive,
-        }
+class AnalysisOptions(AnalysisOptionsModel):
+    pass
 
 
 @dataclass
@@ -65,7 +52,7 @@ class Metric:
     def __init__(self, direction: int = 1, scale: float = 1.0, unit: str = ""):
         self.direction = direction
         self.scale = scale
-        self.unit = ""
+        self.unit = unit
 
     def to_json(self):
         return {"direction": self.direction, "scale": self.scale, "unit": self.unit}
@@ -80,19 +67,19 @@ class Series:
 
     test_name: str
     branch: Optional[str]
-    time: List[int]
+    time: List[int | float]
     metrics: Dict[str, Metric]
-    attributes: Dict[str, List[str]]
+    attributes: Dict[str, List[JsonScalar]]
     data: Dict[str, List[float]]
 
     def __init__(
         self,
         test_name: str,
         branch: Optional[str],
-        time: List[int],
+        time: List[int | float],
         metrics: Dict[str, Metric],
         data: Dict[str, List[float]],
-        attributes: Dict[str, List[str]],
+        attributes: Dict[str, List[JsonScalar]],
     ):
         self.test_name = test_name
         self.branch = branch
@@ -103,7 +90,7 @@ def __init__(
         assert all(len(x) == len(time) for x in data.values())
         assert all(len(x) == len(time) for x in attributes.values())
 
-    def attributes_at(self, index: int) -> Dict[str, str]:
+    def attributes_at(self, index: int) -> Dict[str, JsonScalar]:
         result = {}
         for k, v in self.attributes.items():
             result[k] = v[index]
@@ -124,7 +111,9 @@ def find_by_attribute(self, name: str, value: str) -> List[int]:
                 result.append(i)
         return result
 
-    def analyze(self, options: AnalysisOptions = AnalysisOptions()) -> "AnalyzedSeries":
+    def analyze(self, options: Optional[AnalysisOptions] = None) -> "AnalyzedSeries":
+        if options is None:
+            options = AnalysisOptions()
         logging.info(f"Computing change points for test {self.test_name}...")
         return AnalyzedSeries(self, options)
 
@@ -344,8 +333,8 @@ def branch_name(self) -> Optional[str]:
     def len(self) -> int:
         return len(self.__series.time)
 
-    def time(self) -> List[int]:
-        return [int(t) for t in self.__series.time]
+    def time(self) -> List[int | float]:
+        return list(self.__series.time)
 
     def data(self, metric: str) -> List[float]:
         return [float(d) for d in self.__series.data[metric]]
@@ -353,10 +342,10 @@ def data(self, metric: str) -> List[float]:
     def attributes(self) -> Iterable[str]:
         return self.__series.attributes.keys()
 
-    def attributes_at(self, index: int) -> Dict[str, str]:
+    def attributes_at(self, index: int) -> Dict[str, JsonScalar]:
         return self.__series.attributes_at(index)
 
-    def attribute_values(self, attribute: str) -> List[str]:
+    def attribute_values(self, attribute: str) -> List[JsonScalar]:
         return self.__series.attributes[attribute]
 
     def metric_names(self) -> Iterable[str]:
@@ -371,31 +360,36 @@ def to_json(self):
         for metric_name in self.change_points.metrics():
             change_points_json[metric_name] = []
             for cp in cpbm.select_metrics(metric_name):
-                change_points_json[metric_name].append(cp.to_json(rounded=False))
+                change_points_json[metric_name].append(cp.to_json())
 
         weak_change_points_json = {}
         wcpbm = self.weak_change_points.by_metric()
         for metric_name in self.weak_change_points.metrics():
             weak_change_points_json[metric_name] = []
             for cp in wcpbm.select_metrics(metric_name):
-                weak_change_points_json[metric_name].append(cp.to_json(rounded=False))
+                weak_change_points_json[metric_name].append(cp.to_json())
 
         data_json = {}
         for metric, datapoints in self.__series.data.items():
             data_json[metric] = [float(d) if d is not None else None for d in datapoints]
 
-        return {
+        metrics_json = {}
+        for metric, unit in self.__series.metrics.items():
+            metrics_json[metric] = unit.to_json()
+
+        payload = {
             "test_name": self.test_name(),
             "time": self.time(),
             "change_points_timestamp": self.change_points_timestamp,
             "branch_name": self.branch_name(),
-            "options": self.options.to_json(),
-            "metrics": self.__series.metrics,
+            "options": self.options.model_dump(mode="json"),
+            "metrics": metrics_json,
             "attributes": self.__series.attributes,
-            "data": self.__series.data,
+            "data": data_json,
             "change_points": change_points_json,
             "weak_change_points": weak_change_points_json,
         }
+        return AnalyzedSeriesModel.model_validate(payload).model_dump(mode="json")
 
     @classmethod
     def from_json(cls, analyzed_json):
@@ -445,8 +439,15 @@ def change_points_from_json(change_points_json):
 
         new_metrics = {}
 
-        for metric_name, unit in analyzed_json["metrics"].items():
-            new_metrics[metric_name] = Metric(None, None, unit)
+        for metric_name, metric_json in analyzed_json["metrics"].items():
+            if isinstance(metric_json, dict):
+                new_metrics[metric_name] = Metric(
+                    metric_json.get("direction"),
+                    metric_json.get("scale"),
+                    metric_json.get("unit", ""),
+                )
+            else:
+                new_metrics[metric_name] = Metric(None, None, metric_json)
 
         new_series = Series(
             analyzed_json["test_name"],
@@ -457,11 +458,7 @@ def change_points_from_json(change_points_json):
             analyzed_json["attributes"],
         )
 
-        new_options = AnalysisOptions()
-        new_options.window_len = analyzed_json["options"]["window_len"]
-        new_options.max_pvalue = analyzed_json["options"]["max_pvalue"]
-        new_options.min_magnitude = analyzed_json["options"]["min_magnitude"]
-        new_options.orig_edivisive = analyzed_json["options"]["orig_edivisive"]
+        new_options = AnalysisOptions.model_validate(analyzed_json["options"])
 
         new_change_points = change_points_from_json(analyzed_json["change_points"])
         new_weak_change_points = change_points_from_json(
@@ -472,7 +469,9 @@ def change_points_from_json(change_points_json):
         analyzed_series.weak_change_points = new_weak_change_points
 
         if "change_points_timestamp" in analyzed_json.keys():
-            analyzed_series.change_points_timestamp = analyzed_json["change_points_timestamp"]
+            analyzed_series.change_points_timestamp = _datetime_adapter.validate_python(
+                analyzed_json["change_points_timestamp"]
+            )
             analyzed_series.change_points_by_time = AnalyzedSeries.__group_change_points_by_time(
                 analyzed_series.__series, analyzed_series.change_points
             )
diff --git a/pyproject.toml b/pyproject.toml
index 449f06f9..cf9ad1b6 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -54,6 +54,7 @@ dependencies = [
     "google-cloud-bigquery>=3.38.0",
     "pg8000>=1.31.5",
     "configargparse>=1.7.1",
+    "pydantic>=2,<3",
 
     # For Python 3.10: last series that supports it
     "scipy>=1.15,<1.16; python_version < '3.11'",
diff --git a/tests/change_point_classes_test.py b/tests/change_point_classes_test.py
index c548a570..6e06c0a8 100644
--- a/tests/change_point_classes_test.py
+++ b/tests/change_point_classes_test.py
@@ -50,9 +50,7 @@ def make_stats(left=(1.0, 1.0), right=(5.0, 5.0), pvalue=0.01):
 
 
 def make_cp(metric="m", index=3, left=(1.0, 1.0), right=(5.0, 5.0), pvalue=0.01):
-    return ChangePoint(
-        index=index, qhat=1.0, stats=make_stats(left, right, pvalue), metric=metric
-    )
+    return ChangePoint(index=index, qhat=1.0, stats=make_stats(left, right, pvalue), metric=metric)
 
 
 def make_group(time, metric="m", index=3, commit="sha"):
@@ -306,20 +304,27 @@ def test_changepoint_copy_is_deep():
     assert cp.stats.mean_1 != -1.0
 
 
-def test_changepoint_serializer_rounded_json():
+def test_changepoint_serializer_json_is_precise():
     cp = make_cp(metric="m", index=3, left=(10.0, 10.0), right=(20.0, 20.0), pvalue=0.02)
-    j = ChangePointSerializer(cp).to_json(rounded=True)
+    j = ChangePointSerializer(cp).to_json()
     assert j["metric"] == "m"
     assert j["index"] == 3
-    assert j["forward_change_percent"] == "100"
-    assert all(isinstance(j[k], str) for k in ("magnitude", "mean_before", "pvalue"))
+    assert j["qhat"] == 1.0
+    assert j["forward_change_percent"] == 100.0
+    assert j["magnitude"] == 1.0
+    assert j["mean_before"] == 10.0
+    assert j["mean_after"] == 20.0
+    assert j["pvalue"] == 0.02
 
 
-def test_changepoint_serializer_unrounded_json():
+def test_changepoint_json_is_precise():
     cp = make_cp(metric="m", index=3, left=(10.0, 10.0), right=(20.0, 20.0), pvalue=0.02)
-    j = ChangePointSerializer(cp).to_json(rounded=False)
+    j = cp.to_json()
+    assert j["metric"] == "m"
     assert j["index"] == 3
+    assert j["qhat"] == 1.0
     assert j["forward_change_percent"] == 100.0
+    assert j["magnitude"] == 1.0
     assert j["mean_before"] == 10.0
     assert j["mean_after"] == 20.0
     assert j["pvalue"] == 0.02
@@ -327,7 +332,7 @@ def test_changepoint_serializer_unrounded_json():
 
 def test_changepoint_to_json_delegates_to_serializer():
     cp = make_cp(metric="m", index=3, left=(10.0, 10.0), right=(20.0, 20.0), pvalue=0.02)
-    assert cp.to_json(rounded=False) == ChangePointSerializer(cp).to_json(rounded=False)
+    assert cp.to_json() == ChangePointSerializer(cp).to_json()
 
 
 # ChangePointGroup
@@ -376,6 +381,9 @@ def test_group_to_json():
     assert j["attributes"] == {"commit": "abc"}
     assert isinstance(j["changes"], list) and len(j["changes"]) == 1
     assert j["changes"][0]["metric"] == "m"
+    assert j["changes"][0]["qhat"] == 1.0
+    assert j["changes"][0]["forward_change_percent"] == 400.0
+    assert isinstance(j["changes"][0]["mean_before"], float)
 
 
 def test_group_copy_is_deep():
@@ -505,7 +513,11 @@ def test_bytime_append_out_of_order():
 def test_bytime_get_change_points_for_metric_sparse():
     # 'a' appears at t=1 and t=3, 'b' only at t=2 -> sparse columns
     c = ChangePointsByTime.from_list(
-        [make_group(1.0, "a", index=1), make_group(2.0, "b", index=2), make_group(3.0, "a", index=3)]
+        [
+            make_group(1.0, "a", index=1),
+            make_group(2.0, "b", index=2),
+            make_group(3.0, "a", index=3),
+        ]
     )
     a_points = c.get_change_points_for_metric("a")
     assert [cp.index for cp in a_points] == [1, 3]
@@ -562,7 +574,9 @@ def test_from_dict_is_metric_keyed_and_returns_by_metric():
 
 
 def test_bymetric_list_constructor():
-    bm = ChangePointsByMetric.from_list([make_group(1.0, "a"), make_group(2.0, "a"), make_group(2.0, "b")])
+    bm = ChangePointsByMetric.from_list(
+        [make_group(1.0, "a"), make_group(2.0, "a"), make_group(2.0, "b")]
+    )
     # from_list() returns the class it is called on (asymmetric with from_dict)
     assert isinstance(bm, ChangePointsByMetric)
     assert bm.metrics() == {"a", "b"}
diff --git a/tests/report_test.py b/tests/report_test.py
index 31263b0b..d3d9e6fc 100644
--- a/tests/report_test.py
+++ b/tests/report_test.py
@@ -70,30 +70,50 @@ def test_report(series, change_points):
 def test_json_report(report):
     output = report.produce_report("test_name_from_config", ReportType.JSON)
     obj = json.loads(output)
-    expected = {'test_name_from_config': [{'attributes': {},
-                                           'changes': [{'forward_change_percent': '-11',
-                                                        'backward_change_percent': '12',
-                                                        'index': 4,
-                                                        'magnitude': '0.124108',
-                                                        'mean_after': '1.801429',
-                                                        'mean_before': '2.025000',
-                                                        'metric': 'series2',
-                                                        'pvalue': '0.000000',
-                                                        'stddev_after': '0.026954',
-                                                        'stddev_before': '0.011180'}],
-                                          'time': 4},
-                                          {'attributes': {},
-                                          'changes': [{'forward_change_percent': '-49',
-                                                       'backward_change_percent': '98',
-                                                       'index': 6,
-                                                       'magnitude': '0.977513',
-                                                       'mean_after': '0.504000',
-                                                       'mean_before': '0.996667',
-                                                       'metric': 'series1',
-                                                       'pvalue': '0.000000',
-                                                       'stddev_after': '0.025768',
-                                                       'stddev_before': '0.067495'}],
-                                           'time': 6}]}
+    first_change = obj["test_name_from_config"][0]["changes"][0]
+    assert first_change["forward_change_percent"] == "-11"
+    assert first_change["backward_change_percent"] == "12"
+    assert isinstance(first_change["mean_before"], str)
+    expected = {
+        "test_name_from_config": [
+            {
+                "attributes": {},
+                "changes": [
+                    {
+                        "forward_change_percent": "-11",
+                        "backward_change_percent": "12",
+                        "index": 4,
+                        "magnitude": "0.124108",
+                        "mean_after": "1.801429",
+                        "mean_before": "2.025000",
+                        "metric": "series2",
+                        "pvalue": "0.000000",
+                        "stddev_after": "0.026954",
+                        "stddev_before": "0.011180",
+                    }
+                ],
+                "time": 4,
+            },
+            {
+                "attributes": {},
+                "changes": [
+                    {
+                        "forward_change_percent": "-49",
+                        "backward_change_percent": "98",
+                        "index": 6,
+                        "magnitude": "0.977513",
+                        "mean_after": "0.504000",
+                        "mean_before": "0.996667",
+                        "metric": "series1",
+                        "pvalue": "0.000000",
+                        "stddev_after": "0.025768",
+                        "stddev_before": "0.067495",
+                    }
+                ],
+                "time": 6,
+            },
+        ]
+    }
     assert isinstance(obj, dict)
     assert obj == expected
 
@@ -104,12 +124,20 @@ def test_regression_only_report(report):
 
 
 def test_simplereport_regression_only():
-    s = Series('t', None, list(range(11)),
-               {'a': Metric(1, 1.0), 'b': Metric(1, 1.0)},
-               {'a': [1.02, 0.95, 0.99, 1.00, 1.12, 0.90, 0.50, 0.51, 0.48, 0.48, 0.55],
-                'b': [2.02, 2.03, 2.01, 2.04, 1.82, 1.85, 1.79, 1.81, 1.80, 1.76, 1.78]},
-               {})
-    out = Report(s, s.analyze().change_points_by_time).produce_report('t', ReportType.REGRESSIONS_ONLY)
+    s = Series(
+        "t",
+        None,
+        list(range(11)),
+        {"a": Metric(1, 1.0), "b": Metric(1, 1.0)},
+        {
+            "a": [1.02, 0.95, 0.99, 1.00, 1.12, 0.90, 0.50, 0.51, 0.48, 0.48, 0.55],
+            "b": [2.02, 2.03, 2.01, 2.04, 1.82, 1.85, 1.79, 1.81, 1.80, 1.76, 1.78],
+        },
+        {},
+    )
+    out = Report(s, s.analyze().change_points_by_time).produce_report(
+        "t", ReportType.REGRESSIONS_ONLY
+    )
     print(out)
     assert "Regressions" in out
     assert "-11.0" in out
diff --git a/tests/series_test.py b/tests/series_test.py
index cab900a9..0497380e 100644
--- a/tests/series_test.py
+++ b/tests/series_test.py
@@ -15,12 +15,16 @@
 # specific language governing permissions and limitations
 # under the License.
 
+import json
 import time
+from datetime import datetime
 from random import random
 
 import pytest
+from pydantic import ValidationError
 
 from otava.change_point_divisive.base import ChangePointSerializer
+from otava.serialization import AnalysisOptionsModel, AnalyzedSeriesModel
 from otava.series import AnalysisOptions, AnalyzedSeries, Metric, Series
 
 
@@ -45,6 +49,28 @@ def test_change_point_detection():
     assert cps._change_points[1].changes["series1"].metric == "series1"
 
 
+def test_analysis_options_is_pydantic_model():
+    options = AnalysisOptions(
+        window_len="25",
+        max_pvalue="0.05",
+        min_magnitude=1,
+        orig_edivisive=True,
+    )
+
+    assert isinstance(options, AnalysisOptionsModel)
+    assert options.model_dump(mode="json") == {
+        "window_len": 25,
+        "max_pvalue": 0.05,
+        "min_magnitude": 1.0,
+        "orig_edivisive": True,
+    }
+
+
+def test_analysis_options_rejects_unknown_fields():
+    with pytest.raises(ValidationError):
+        AnalysisOptions(no_such_option=True)
+
+
 def test_change_point_detection_many():
     series_3 = [
         1,
@@ -268,6 +294,172 @@ def test_analyzed_series_json_round_trip():
     assert restored.to_json()["weak_change_points"] == payload["weak_change_points"]
 
 
+def test_analyzed_series_json_round_trip_through_json_module():
+    series_1 = [1.02, 0.95, 0.99, 1.00, 1.12, 0.90, 0.50, 0.51, 0.48, 0.48, 0.55]
+    series_2 = [2.02, 2.03, 2.01, 2.04, 1.82, 1.85, 1.79, 1.81, 1.80, 1.76, 1.78]
+    time = list(range(len(series_1)))
+    series = Series(
+        "test",
+        branch=None,
+        time=time,
+        metrics={"series1": Metric(1, 1.0), "series2": Metric(1, 1.0)},
+        data={"series1": series_1, "series2": series_2},
+        attributes={},
+    )
+
+    analyzed_series = series.analyze()
+    analyzed_series.append(
+        time=[len(time)], new_data={"series1": [0.5], "series2": [1.97]}, attributes={}
+    )
+
+    payload = analyzed_series.to_json()
+    decoded = json.loads(json.dumps(payload))
+    restored = AnalyzedSeries.from_json(decoded)
+
+    assert isinstance(restored.change_points_timestamp, datetime)
+    assert restored.to_json()["change_points"] == decoded["change_points"]
+    assert restored.to_json()["weak_change_points"] == decoded["weak_change_points"]
+
+
+def test_analyzed_series_json_round_trip_preserves_json_scalar_attributes():
+    values = [1.02, 0.95, 0.99, 1.00, 1.12, 0.90, 0.50, 0.51, 0.48, 0.48, 0.55]
+    attributes = {
+        "commit": [None] * len(values),
+        "build": list(range(len(values))),
+        "passed": [True] * len(values),
+    }
+    series = Series(
+        "test",
+        branch=None,
+        time=list(range(len(values))),
+        metrics={"series": Metric(1, 1.0)},
+        data={"series": values},
+        attributes=attributes,
+    )
+
+    decoded = json.loads(json.dumps(series.analyze().to_json()))
+    restored = AnalyzedSeries.from_json(decoded)
+
+    assert restored.to_json()["attributes"] == attributes
+    assert restored.to_json()["change_points"]["series"][0]["attributes"] == {
+        "commit": None,
+        "build": 6,
+        "passed": True,
+    }
+
+
+def test_analyzed_series_json_round_trip_preserves_fractional_timestamps():
+    values = [1.02, 0.95, 0.99, 1.00, 1.12, 0.90, 0.50, 0.51, 0.48, 0.48, 0.55]
+    timestamps = [1_700_000_000.25 + index for index in range(len(values))]
+    series = Series(
+        "test",
+        branch=None,
+        time=timestamps,
+        metrics={"series": Metric(1, 1.0)},
+        data={"series": values},
+        attributes={},
+    )
+
+    payload = series.analyze().to_json()
+    restored = AnalyzedSeries.from_json(json.loads(json.dumps(payload)))
+
+    assert payload["time"] == timestamps
+    assert restored.time() == timestamps
+    assert restored.to_json()["change_points"]["series"][0]["time"] == timestamps[6]
+
+
+def test_analyzed_series_json_round_trip_preserves_integer_timestamp_types():
+    values = [1.02, 0.95, 0.99, 1.00, 1.12, 0.90, 0.50, 0.51, 0.48, 0.48, 0.55]
+    timestamps = list(range(len(values)))
+    series = Series(
+        "test",
+        branch=None,
+        time=timestamps,
+        metrics={"series": Metric(1, 1.0)},
+        data={"series": values},
+        attributes={},
+    )
+
+    payload = series.analyze().to_json()
+    restored_payload = AnalyzedSeries.from_json(payload).to_json()
+
+    assert all(type(timestamp) is int for timestamp in restored_payload["time"])
+    assert type(restored_payload["change_points"]["series"][0]["time"]) is int
+
+
+def test_analyzed_series_json_round_trip_preserves_current_and_legacy_metric_units():
+    series = Series(
+        "test",
+        branch=None,
+        time=[1, 2],
+        metrics={"latency": Metric(1, 1.0, "ms")},
+        data={"latency": [1.0, 2.0]},
+        attributes={},
+    )
+
+    payload = series.analyze().to_json()
+    current = AnalyzedSeries.from_json(payload)
+    payload["metrics"]["latency"] = "seconds"
+    legacy = AnalyzedSeries.from_json(payload)
+
+    assert (
+        current.metric("latency").unit,
+        current.to_json()["metrics"]["latency"]["unit"],
+        legacy.metric("latency").unit,
+        legacy.to_json()["metrics"]["latency"]["unit"],
+    ) == ("ms", "ms", "seconds", "seconds")
+
+
+def test_analyzed_series_from_json_validates_options_with_pydantic():
+    series_1 = [1.02, 0.95, 0.99, 1.00, 1.12, 0.90, 0.50, 0.51, 0.48, 0.48, 0.55]
+    time = list(range(len(series_1)))
+    series = Series(
+        "test",
+        branch=None,
+        time=time,
+        metrics={"series1": Metric(1, 1.0)},
+        data={"series1": series_1},
+        attributes={},
+    )
+
+    payload = series.analyze().to_json()
+    payload["options"]["window_len"] = "25"
+    restored = AnalyzedSeries.from_json(payload)
+
+    assert isinstance(restored.options, AnalysisOptions)
+    assert restored.options.window_len == 25
+
+
+def test_analyzed_series_json_uses_pydantic_model_shape():
+    series_1 = [1.02, 0.95, 0.99, 1.00, 1.12, 0.90, 0.50, 0.51, 0.48, 0.48, 0.55]
+    series_2 = [2.02, 2.03, 2.01, 2.04, 1.82, 1.85, 1.79, 1.81, 1.80, 1.76, 1.78]
+    time = list(range(len(series_1)))
+    series = Series(
+        "test",
+        branch=None,
+        time=time,
+        metrics={"series1": Metric(1, 1.0), "series2": Metric(1, 1.0)},
+        data={"series1": series_1, "series2": series_2},
+        attributes={},
+    )
+
+    analyzed_series = series.analyze()
+    analyzed_series.append(
+        time=[len(time)], new_data={"series1": [0.5], "series2": [1.97]}, attributes={}
+    )
+
+    payload = analyzed_series.to_json()
+    model = AnalyzedSeriesModel.model_validate(payload)
+    dumped = model.model_dump(mode="python")
+
+    change = dumped["change_points"]["series2"][0]["changes"][0]
+    weak_change = dumped["weak_change_points"]["series2"][1]["changes"][0]
+    assert isinstance(change["mean_before"], float)
+    assert isinstance(change["forward_change_percent"], float)
+    assert isinstance(weak_change["pvalue"], float)
+    assert AnalyzedSeries.from_json(dumped).to_json()["change_points"] == dumped["change_points"]
+
+
 def test_validate():
     series_1 = [1.02, 0.95, 0.99, 1.00, 1.12, 0.90, 0.50, 0.51, 0.48, 0.48, 0.55]
     series_2 = [2.02, 2.03, 2.01, 2.04, 1.82, 1.85, 1.79, 1.81, 1.80, 1.76, 1.78]
diff --git a/uv.lock b/uv.lock
index f9001c49..5802fbbb 100644
--- a/uv.lock
+++ b/uv.lock
@@ -8,6 +8,15 @@ resolution-markers = [
     "python_full_version < '3.11'",
 ]
 
+[[package]]
+name = "annotated-types"
+version = "0.8.0"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/5f/56/a8120250d128bed162cd73c76d45f6ef9991f3e068f62a8ee060afa3104a/annotated_types-0.8.0.tar.gz", hash = "sha256:13b2beaad985e05e2d6407ee4c4f35590b11f8d693a258a561055cac8f64cab7", size = 15893, upload-time = "2026-07-23T20:16:13.995Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/99/91/8acff4f5e50511b911bbccb72b8628a49c68ce14148cd9f6431094859a90/annotated_types-0.8.0-py3-none-any.whl", hash = "sha256:f072f4d804ea359e4eaf198b1af7a8b0943881a87f31bb764f8bf219bb9419e0", size = 13427, upload-time = "2026-07-23T20:16:12.938Z" },
+]
+
 [[package]]
 name = "apache-otava"
 version = "0.8.0"
@@ -19,6 +28,7 @@ dependencies = [
     { name = "numpy", version = "2.2.6", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.14'" },
     { name = "numpy", version = "2.3.5", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.14'" },
     { name = "pg8000" },
+    { name = "pydantic" },
     { name = "pystache" },
     { name = "python-dateutil" },
     { name = "requests" },
@@ -62,6 +72,7 @@ requires-dist = [
     { name = "numpy", marker = "python_full_version >= '3.14'", specifier = ">=2.3.2,<2.4" },
     { name = "pg8000", specifier = ">=1.31.5" },
     { name = "pre-commit", marker = "extra == 'dev'", specifier = "==4.5.0" },
+    { name = "pydantic", specifier = ">=2,<3" },
     { name = "pystache", specifier = ">=0.6.8" },
     { name = "pytest", marker = "extra == 'dev'", specifier = ">=9.0.1" },
     { name = "pytest-benchmark", marker = "extra == 'dev'", specifier = ">=5.2.3" },
@@ -1044,6 +1055,137 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/d7/27/a58ddaf8c588a3ef080db9d0b7e0b97215cee3a45df74f3a94dbbf5c893a/pycodestyle-2.14.0-py2.py3-none-any.whl", hash = "sha256:dd6bf7cb4ee77f8e016f9c8e74a35ddd9f67e1d5fd4184d86c3b98e07099f42d", size = 31594, upload-time = "2025-06-20T18:49:47.491Z" },
 ]
 
+[[package]]
+name = "pydantic"
+version = "2.13.4"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "annotated-types" },
+    { name = "pydantic-core" },
+    { name = "typing-extensions" },
+    { name = "typing-inspection" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/18/a5/b60d21ac674192f8ab0ba4e9fd860690f9b4a6e51ca5df118733b487d8d6/pydantic-2.13.4.tar.gz", hash = "sha256:c40756b57adaa8b1efeeced5c196f3f3b7c435f90e84ea7f443901bec8099ef6", size = 844775, upload-time = "2026-05-06T13:43:05.343Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/fd/7b/122376b1fd3c62c1ed9dc80c931ace4844b3c55407b6fb2d199377c9736f/pydantic-2.13.4-py3-none-any.whl", hash = "sha256:45a282cde31d808236fd7ea9d919b128653c8b38b393d1c4ab335c62924d9aba", size = 472262, upload-time = "2026-05-06T13:43:02.641Z" },
+]
+
+[[package]]
+name = "pydantic-core"
+version = "2.46.4"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "typing-extensions" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/9d/56/921726b776ace8d8f5db44c4ef961006580d91dc52b803c489fafd1aa249/pydantic_core-2.46.4.tar.gz", hash = "sha256:62f875393d7f270851f20523dd2e29f082bcc82292d66db2b64ea71f64b6e1c1", size = 471464, upload-time = "2026-05-06T13:37:06.98Z" }
+wheels = [
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