diff --git a/pyproject.toml b/pyproject.toml
index 27eeee01f5..7ded8bc460 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -22,11 +22,12 @@ classifiers = [
 ]
 dependencies = [
   "scikit-learn",
-  "numpy<2",  # https://github.com/TutteInstitute/fast_hdbscan/issues/17#issuecomment-2380859314
+  "numpy!=2.0.0",  # https://github.com/lmcinnes/umap/issues/1138
   "pandas>=1.0",
   "jinja2",
   "umap-learn",
-  "fast-hdbscan",
+  "hdbscan>=0.8.38",
+  "numba>=0.60.0",  # https://github.com/astral-sh/uv/issues/6281
   "starlette",
   "uvicorn",
   "psutil",
@@ -385,7 +386,7 @@ exclude = [
 
 [[tool.mypy.overrides]]
 module = [
-  "fast_hdbscan",
+  "hdbscan",
   "umap",
   "numba.*",
   "scipy.*",
diff --git a/src/phoenix/pointcloud/clustering.py b/src/phoenix/pointcloud/clustering.py
index 6ed4b23ae4..afdc8bbc3f 100644
--- a/src/phoenix/pointcloud/clustering.py
+++ b/src/phoenix/pointcloud/clustering.py
@@ -17,7 +17,7 @@ class Hdbscan:
     cluster_selection_epsilon: float = 0.0
 
     def find_clusters(self, mat: Matrix) -> List[RawCluster]:
-        from fast_hdbscan import HDBSCAN
+        from hdbscan import HDBSCAN
 
         cluster_ids: npt.NDArray[np.int_] = HDBSCAN(**asdict(self)).fit_predict(mat)
         ans: List[RawCluster] = [set() for _ in range(np.max(cluster_ids) + 1)]
diff --git a/src/phoenix/pointcloud/projectors.py b/src/phoenix/pointcloud/projectors.py
index 4ebbbbdb6a..39316e50da 100644
--- a/src/phoenix/pointcloud/projectors.py
+++ b/src/phoenix/pointcloud/projectors.py
@@ -6,12 +6,6 @@
 import numpy.typing as npt
 from typing_extensions import TypeAlias
 
-with warnings.catch_warnings():
-    from numba.core.errors import NumbaWarning
-
-    warnings.simplefilter("ignore", category=NumbaWarning)
-    from umap import UMAP
-
 Matrix: TypeAlias = npt.NDArray[np.float64]
 
 
@@ -25,6 +19,11 @@ class Umap:
     min_dist: float = 0.1
 
     def project(self, mat: Matrix, n_components: int) -> Matrix:
+        with warnings.catch_warnings():
+            from numba.core.errors import NumbaWarning
+
+            warnings.simplefilter("ignore", category=NumbaWarning)
+            from umap import UMAP
         config = asdict(self)
         config["n_components"] = n_components
         if len(mat) <= n_components: