diff --git a/web/apps/photos/src/services/face/f-index.ts b/web/apps/photos/src/services/face/f-index.ts
index cee2bbc5c..db054ac29 100644
--- a/web/apps/photos/src/services/face/f-index.ts
+++ b/web/apps/photos/src/services/face/f-index.ts
@@ -7,13 +7,11 @@ import { faceEmbeddings, mobileFaceNetFaceSize } from "services/face/embed";
 import {
     DetectedFace,
     Face,
-    MLSyncContext,
     MLSyncFileContext,
     type FaceAlignment,
 } from "services/face/types";
 import { imageBitmapToBlob, warpAffineFloat32List } from "utils/image";
 import { detectBlur } from "./blur";
-import { clusterFaces } from "./cluster";
 import { getFaceCrop } from "./crop";
 import {
     fetchImageBitmap,
@@ -161,51 +159,6 @@ export const saveFaceCrop = async (imageBitmap: ImageBitmap, face: Face) => {
     return blob;
 };
 
-export const getAllSyncedFacesMap = async (syncContext: MLSyncContext) => {
-    if (syncContext.allSyncedFacesMap) {
-        return syncContext.allSyncedFacesMap;
-    }
-
-    syncContext.allSyncedFacesMap = await mlIDbStorage.getAllFacesMap();
-    return syncContext.allSyncedFacesMap;
-};
-
-export const runFaceClustering = async (
-    syncContext: MLSyncContext,
-    allFaces: Array<Face>,
-) => {
-    // await this.init();
-
-    if (!allFaces || allFaces.length < 50) {
-        log.info(
-            `Skipping clustering since number of faces (${allFaces.length}) is less than the clustering threshold (50)`,
-        );
-        return;
-    }
-
-    log.info("Running clustering allFaces: ", allFaces.length);
-    syncContext.mlLibraryData.faceClusteringResults = await clusterFaces(
-        allFaces.map((f) => Array.from(f.embedding)),
-    );
-    syncContext.mlLibraryData.faceClusteringMethod = {
-        value: "Hdbscan",
-        version: 1,
-    };
-    log.info(
-        "[MLService] Got face clustering results: ",
-        JSON.stringify(syncContext.mlLibraryData.faceClusteringResults),
-    );
-
-    // syncContext.faceClustersWithNoise = {
-    //     clusters: syncContext.faceClusteringResults.clusters.map(
-    //         (faces) => ({
-    //             faces,
-    //         })
-    //     ),
-    //     noise: syncContext.faceClusteringResults.noise,
-    // };
-};
-
 export const regenerateFaceCrop = async (faceID: string) => {
     const fileID = Number(faceID.split("-")[0]);
     const personFace = await mlIDbStorage.getFace(fileID, faceID);
diff --git a/web/apps/photos/src/services/face/people.ts b/web/apps/photos/src/services/face/people.ts
index 16c511c0b..f795e94f1 100644
--- a/web/apps/photos/src/services/face/people.ts
+++ b/web/apps/photos/src/services/face/people.ts
@@ -1,10 +1,8 @@
+import log from "@/next/log";
 import mlIDbStorage from "services/face/db";
 import { Face, MLSyncContext, Person } from "services/face/types";
-import {
-    getAllSyncedFacesMap,
-    runFaceClustering,
-    saveFaceCrop,
-} from "./f-index";
+import { clusterFaces } from "./cluster";
+import { saveFaceCrop } from "./f-index";
 import { fetchImageBitmap, getLocalFile } from "./image";
 
 export const syncPeopleIndex = async (syncContext: MLSyncContext) => {
@@ -16,7 +14,9 @@ export const syncPeopleIndex = async (syncContext: MLSyncContext) => {
     // 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 getAllSyncedFacesMap(syncContext);
+    const allFacesMap =
+        syncContext.allSyncedFacesMap ??
+        (syncContext.allSyncedFacesMap = await mlIDbStorage.getAllFacesMap());
     const allFaces = [...allFacesMap.values()].flat();
 
     await runFaceClustering(syncContext, allFaces);
@@ -25,6 +25,42 @@ export const syncPeopleIndex = async (syncContext: MLSyncContext) => {
     await mlIDbStorage.setIndexVersion("people", filesVersion);
 };
 
+const runFaceClustering = async (
+    syncContext: MLSyncContext,
+    allFaces: Array<Face>,
+) => {
+    // await this.init();
+
+    if (!allFaces || allFaces.length < 50) {
+        log.info(
+            `Skipping clustering since number of faces (${allFaces.length}) is less than the clustering threshold (50)`,
+        );
+        return;
+    }
+
+    log.info("Running clustering allFaces: ", allFaces.length);
+    syncContext.mlLibraryData.faceClusteringResults = await clusterFaces(
+        allFaces.map((f) => Array.from(f.embedding)),
+    );
+    syncContext.mlLibraryData.faceClusteringMethod = {
+        value: "Hdbscan",
+        version: 1,
+    };
+    log.info(
+        "[MLService] Got face clustering results: ",
+        JSON.stringify(syncContext.mlLibraryData.faceClusteringResults),
+    );
+
+    // syncContext.faceClustersWithNoise = {
+    //     clusters: syncContext.faceClusteringResults.clusters.map(
+    //         (faces) => ({
+    //             faces,
+    //         })
+    //     ),
+    //     noise: syncContext.faceClusteringResults.noise,
+    // };
+};
+
 const syncPeopleFromClusters = async (
     syncContext: MLSyncContext,
     allFacesMap: Map<number, Array<Face>>,