diff --git a/web/apps/photos/src/services/face/people.ts b/web/apps/photos/src/services/face/people.ts
new file mode 100644
index 000000000..8a0f0e969
--- /dev/null
+++ b/web/apps/photos/src/services/face/people.ts
@@ -0,0 +1,81 @@
+import mlIDbStorage from "services/face/db";
+import { Face, MLSyncContext, Person } from "services/face/types";
+import FaceService from "../machineLearning/faceService";
+import { fetchImageBitmap, getLocalFile } from "./image";
+
+export const syncPeopleIndex = async (syncContext: MLSyncContext) => {
+    const filesVersion = await mlIDbStorage.getIndexVersion("files");
+    if (filesVersion <= (await mlIDbStorage.getIndexVersion("people"))) {
+        return;
+    }
+
+    // TODO: have faces addresable through fileId + faceId
+    // to avoid index based addressing, which is prone to wrong results
+    // one way could be to match nearest face within threshold in the file
+    const allFacesMap = await FaceService.getAllSyncedFacesMap(syncContext);
+    const allFaces = getAllFacesFromMap(allFacesMap);
+
+    await FaceService.runFaceClustering(syncContext, allFaces);
+    await syncPeopleFromClusters(syncContext, allFacesMap, allFaces);
+
+    await mlIDbStorage.setIndexVersion("people", filesVersion);
+};
+
+const syncPeopleFromClusters = async (
+    syncContext: MLSyncContext,
+    allFacesMap: Map<number, Array<Face>>,
+    allFaces: Array<Face>,
+) => {
+    const clusters = syncContext.mlLibraryData.faceClusteringResults?.clusters;
+    if (!clusters || clusters.length < 1) {
+        return;
+    }
+
+    for (const face of allFaces) {
+        face.personId = undefined;
+    }
+    await mlIDbStorage.clearAllPeople();
+    for (const [index, cluster] of clusters.entries()) {
+        const faces = cluster.map((f) => allFaces[f]).filter((f) => f);
+
+        // TODO: take default display face from last leaves of hdbscan clusters
+        const personFace = faces.reduce((best, face) =>
+            face.detection.probability > best.detection.probability
+                ? face
+                : best,
+        );
+
+        if (personFace && !personFace.crop?.cacheKey) {
+            const file = await getLocalFile(personFace.fileId);
+            const imageBitmap = await fetchImageBitmap(file);
+            await FaceService.saveFaceCrop(
+                imageBitmap,
+                personFace,
+                syncContext,
+            );
+        }
+
+        const person: Person = {
+            id: index,
+            files: faces.map((f) => f.fileId),
+            displayFaceId: personFace?.id,
+            faceCropCacheKey: personFace?.crop?.cacheKey,
+        };
+
+        await mlIDbStorage.putPerson(person);
+
+        faces.forEach((face) => {
+            face.personId = person.id;
+        });
+        // log.info("Creating person: ", person, faces);
+    }
+
+    await mlIDbStorage.updateFaces(allFacesMap);
+};
+
+
+function getAllFacesFromMap(allFacesMap: Map<number, Array<Face>>) {
+    const allFaces = [...allFacesMap.values()].flat();
+
+    return allFaces;
+}