diff --git a/swh/storage/algos/discovery.py b/swh/storage/algos/discovery.py
new file mode 100644
--- /dev/null
+++ b/swh/storage/algos/discovery.py
@@ -0,0 +1,90 @@
+# Copyright (C) 2022 The Software Heritage developers
+# See the AUTHORS file at the top-level directory of this distribution
+# License: GNU General Public License version 3, or any later version
+# See top-level LICENSE file for more information
+
+import logging
+import random
+
+from swh.model.discovery import (
+    SAMPLE_SIZE,
+    ArchiveDiscoveryInterface,
+    BaseDiscoveryGraph,
+    Sample,
+)
+from swh.model.from_disk import model
+
+logger = logging.getLogger(__name__)
+
+
+class RandomDirSamplingDiscoveryGraph(BaseDiscoveryGraph):
+    """Use a random sampling using only directories.
+
+    This allows us to find a statistically good spread of entries in the graph
+    with a smaller population than using all types of entries. When there are
+    no more directories, only contents or skipped contents are undecided if any
+    are left: we send them directly to the storage since they should be few and
+    their structure flat."""
+
+    async def get_sample(self) -> Sample:
+        if self._undecided_directories:
+            if len(self._undecided_directories) <= SAMPLE_SIZE:
+                return Sample(
+                    contents=set(),
+                    skipped_contents=set(),
+                    directories=set(self._undecided_directories),
+                )
+            sample = random.sample(self._undecided_directories, SAMPLE_SIZE)
+            directories = {o for o in sample}
+            return Sample(
+                contents=set(), skipped_contents=set(), directories=directories
+            )
+
+        contents = set()
+        skipped_contents = set()
+
+        for sha1 in self.undecided:
+            obj = self._all_contents[sha1]
+            obj_type = obj.object_type
+            if obj_type == model.Content.object_type:
+                contents.add(sha1)
+            elif obj_type == model.SkippedContent.object_type:
+                skipped_contents.add(sha1)
+            else:
+                raise TypeError(f"Unexpected object type {obj_type}")
+
+        return Sample(
+            contents=contents, skipped_contents=skipped_contents, directories=set()
+        )
+
+
+async def filter_known_objects(archive: ArchiveDiscoveryInterface):
+    """Filter ``archive``'s ``contents``, ``skipped_contents`` and ``directories``
+    to only return those that are unknown to the SWH archive using a discovery
+    algorithm."""
+    contents = archive.contents
+    skipped_contents = archive.skipped_contents
+    directories = archive.directories
+
+    contents_count = len(contents)
+    skipped_contents_count = len(skipped_contents)
+    directories_count = len(directories)
+
+    graph = RandomDirSamplingDiscoveryGraph(contents, skipped_contents, directories)
+
+    while graph.undecided:
+        sample = await graph.get_sample()
+        await graph.do_query(archive, sample)
+
+    contents = [c for c in contents if c.sha1_git in graph.unknown]
+    skipped_contents = [c for c in skipped_contents if c.sha1_git in graph.unknown]
+    directories = [c for c in directories if c.id in graph.unknown]
+
+    logger.debug(
+        "Filtered out %d contents, %d skipped contents and %d directories",
+        contents_count - len(contents),
+        skipped_contents_count - len(skipped_contents),
+        directories_count - len(directories),
+    )
+
+    return (contents, skipped_contents, directories)