diff --git a/recognization/code/eval_identity.py b/recognization/code/eval_identity.py
index 01e3dfe..4a4ba5e 100644
--- a/recognization/code/eval_identity.py
+++ b/recognization/code/eval_identity.py
@@ -3,9 +3,9 @@
 The original matcher is a candidate final architecture, not just a baseline.
 Every lane is scored the same way, on the same crops, at the same resolutions:
 
+    local          RootSIFT pyramid + OCR text lane (the shipped default)
     matcher        full-catalog SIFT/ORB/BRISK + RANSAC (the original demo)
     gallery        DINOv2 embedding, raw or with the trained head
-    hybrid-verify  DINO shortlist, then the matcher re-ranks inside it
 
 Reported per lane, as four separate ceilings rather than one conflated number:
 
@@ -56,7 +56,7 @@ UNKNOWN = "unknown"
 # Two independent label passes disagreed here, so the row is not ground truth.
 # Scoring it would be scoring a coin flip.
 EXCLUDE = "exclude"
-LANES = ("matcher", "gallery", "hybrid-verify")
+LANES = ("local", "matcher", "gallery", "hybrid-verify")
 # A single SKU above this share of accepts is the failure the last audit found:
 # every dark package collapsing onto one enrolled product.
 HUB_SHARE = 0.30
diff --git a/recognization/code/eval_live.py b/recognization/code/eval_live.py
index 56eeeca..02b4c78 100644
--- a/recognization/code/eval_live.py
+++ b/recognization/code/eval_live.py
@@ -11,7 +11,7 @@ store was enrolled; scoring them is training-set accuracy.
 
     python code/eval_live.py RECORDING_DIR [--stock-dir DIR] [--labels PATH]
                               [--json PATH] [--iou 0.5]
-                              [--replay] [--identity matcher|gallery] [--device cpu|mps|cuda]
+                              [--replay] [--identity matcher|local|gallery] [--device cpu|mps|cuda]
 
 Prints a human count table and writes the same report as JSON (default
 <recording>/eval_live.json). Missing input exits 2 with {"error": ...} on