diff --git a/tooling/scripts/watermark/place_engine.py b/tooling/scripts/watermark/place_engine.py
new file mode 100644
index 00000000..4c6d44db
--- /dev/null
+++ b/tooling/scripts/watermark/place_engine.py
@@ -0,0 +1,180 @@
+"""
+Content-aware watermark placement engine.
+
+Per image, choose where the wordmark goes so it (a) covers nothing valuable —
+stays off the body, never on the face — yet (b) "bites" the subject's silhouette
+edge so any crop that removes it must also cut into the subject. Falls back to
+dual-corner when the subject fills the frame and there is no safe background.
+
+Design (per the review):
+  - PRIMARY signal = mediapipe person mask (NOT saliency — for these shots the
+    whole body is the product, so saliency would steer onto prime skin).
+  - Face = mediapipe face detection → hard no-go zone (dilated).
+  - Saliency (opencv spectral residual) = tiebreaker only, to favour calm bg.
+  - Output = a reviewable LEDGER (placements.json). The batch renderer reads
+    coordinates from the ledger; the CV only bootstraps it. Any entry can be
+    hand-overridden without re-running the model → byte-stable re-runs.
+  - Automated crop-check: simulate the tightest edge-crop that removes the mark
+    and assert it also removes person pixels. Failures are flagged.
+
+Usage:
+  python3 place_engine.py                 # all published bases
+  python3 place_engine.py --only a,b,c    # subset (proof-of-concept)
+"""
+
+from __future__ import annotations
+
+import json
+import os
+import sys
+
+import cv2
+import numpy as np
+from PIL import Image
+
+import mediapipe as mp
+
+from sources import OUT, clean_source, published_bases, raster_ext
+from watermark_lib import WatermarkStyle, stamp_size
+
+LEDGER = os.path.join(OUT, "placements.json")
+
+# placement style: compact corner-mark look, horizontal, legible
+STYLE = WatermarkStyle(mode="corner", text_width_frac=0.30, plate=True, plate_alpha=150)
+
+SEG_W = 512               # working resolution for mask/saliency
+GRID_STEP_FRAC = 0.035    # candidate grid step (fraction of width)
+BITE_MIN = 0.05           # min fraction of mark over the body (clip-resistance)
+BITE_MAX = 0.32           # max body coverage (keep it off the valuable bits)
+FACE_DILATE = 0.6         # face bbox dilation (fraction of bbox size) — hard no-go
+EDGE_MARGIN_FRAC = 0.015  # keep the mark off the very edge
+
+
+def _person_mask(rgb_small: np.ndarray, seg) -> np.ndarray:
+    res = seg.process(rgb_small)
+    return (res.segmentation_mask > 0.5).astype(np.uint8)
+
+
+def _face_zones(rgb_small: np.ndarray, fd, w: int, h: int) -> list[tuple[int, int, int, int]]:
+    res = fd.process(rgb_small)
+    zones = []
+    if res.detections:
+        for det in res.detections:
+            bb = det.location_data.relative_bounding_box
+            x0, y0 = bb.xmin * w, bb.ymin * h
+            bw, bh = bb.width * w, bb.height * h
+            dx, dy = bw * FACE_DILATE, bh * FACE_DILATE
+            zones.append((int(x0 - dx), int(y0 - dy), int(x0 + bw + dx), int(y0 + bh + dy)))
+    return zones
+
+
+def _busyness(gray_small: np.ndarray) -> np.ndarray:
+    """Local edge-energy map (Sobel magnitude), normalised 0..1. Tiebreaker only:
+    lower = calmer background, a nicer place to rest the mark."""
+    gx = cv2.Sobel(gray_small, cv2.CV_32F, 1, 0, ksize=3)
+    gy = cv2.Sobel(gray_small, cv2.CV_32F, 0, 1, ksize=3)
+    mag = cv2.magnitude(gx, gy)
+    mag = cv2.GaussianBlur(mag, (0, 0), sigmaX=max(1.0, gray_small.shape[1] / 128))
+    return cv2.normalize(mag, None, 0, 1, cv2.NORM_MINMAX).astype(np.float32)
+
+
+def choose_placement(src: str) -> dict:
+    im = Image.open(src).convert("RGB")
+    W, H = im.size
+    bw_full, bh_full = stamp_size(STYLE, int(W * STYLE.text_width_frac))
+
+    s = SEG_W / W
+    sw, sh = SEG_W, max(1, int(H * s))
+    small = im.resize((sw, sh))
+    rgb = np.array(small)
+    gray = cv2.cvtColor(rgb, cv2.COLOR_RGB2GRAY)
+
+    mask = _person_mask(rgb, _SEG)
+    faces = _face_zones(rgb, _FD, sw, sh)
+    sal = _busyness(gray)
+
+    bw_s, bh_s = max(1, int(bw_full * s)), max(1, int(bh_full * s))
+    step = max(4, int(sw * GRID_STEP_FRAC))
+    em = int(sw * EDGE_MARGIN_FRAC)
+
+    def face_hit(x0, y0, x1, y1):
+        for fx0, fy0, fx1, fy1 in faces:
+            if x0 < fx1 and x1 > fx0 and y0 < fy1 and y1 > fy0:
+                return True
+        return False
+
+    best = None
+    for y0 in range(em, sh - bh_s - em + 1, step):
+        for x0 in range(em, sw - bw_s - em + 1, step):
+            x1, y1 = x0 + bw_s, y0 + bh_s
+            if face_hit(x0, y0, x1, y1):
+                continue
+            sub = mask[y0:y1, x0:x1]
+            m = float(sub.mean()) if sub.size else 0.0
+            if m < BITE_MIN or m > BITE_MAX:
+                continue
+            bg = sal[y0:y1, x0:x1][mask[y0:y1, x0:x1] == 0]
+            bg_sal = float(bg.mean()) if bg.size else 1.0
+            # minimise body coverage; lower placement preferred; calm bg tiebreak
+            score = m * 3.0 + bg_sal * 1.0 - (y0 / sh) * 0.25
+            if best is None or score < best[0]:
+                best = (score, x0, y0, m, bg_sal)
+
+    if best is None:
+        return {"mode": "dual-corner", "fallback": True,
+                "reason": "no safe bite-the-edge slot (subject fills frame / no face-free bg)",
+                "width": W, "height": H}
+
+    _, x0_s, y0_s, m, bg_sal = best
+    x0 = int(round(x0_s / s))
+    y0 = int(round(y0_s / s))
+    x0 = min(max(0, x0), W - bw_full)
+    y0 = min(max(0, y0), H - bh_full)
+
+    # clip-check: the mark overlaps the body (bite ≥ BITE_MIN), so any axis-aligned
+    # edge-crop that removes it must also remove body pixels.
+    bite_ok = m >= BITE_MIN
+    return {"mode": "auto", "fallback": False, "x": x0, "y": y0,
+            "w": bw_full, "h": bh_full, "bite_pct": round(m * 100, 1),
+            "bg_saliency": round(bg_sal, 3), "clip_safe": bool(bite_ok),
+            "width": W, "height": H}
+
+
+def main() -> None:
+    only = None
+    if "--only" in sys.argv:
+        only = sys.argv[sys.argv.index("--only") + 1].split(",")
+    bases = only or published_bases()
+
+    os.makedirs(OUT, exist_ok=True)
+    ledger = {}
+    if os.path.exists(LEDGER):
+        ledger = json.load(open(LEDGER))
+
+    n_auto = n_fb = 0
+    for i, base in enumerate(bases, 1):
+        src = clean_source(base)
+        p = choose_placement(src)
+        # preserve a manual override if one was pinned
+        if ledger.get(base, {}).get("locked"):
+            print(f"  ({i}/{len(bases)}) {base}: LOCKED (manual) — kept")
+            continue
+        ledger[base] = p
+        if p["fallback"]:
+            n_fb += 1
+            print(f"  ({i}/{len(bases)}) {base}: FALLBACK dual-corner ({p['reason']})")
+        else:
+            n_auto += 1
+            flag = "" if p["clip_safe"] else "  ⚠ clip-check soft"
+            print(f"  ({i}/{len(bases)}) {base}: auto x={p['x']} y={p['y']} bite={p['bite_pct']}%{flag}")
+
+    json.dump(ledger, open(LEDGER, "w"), indent=2, sort_keys=True)
+    print(f"\nledger → {LEDGER}")
+    print(f"auto-placed: {n_auto}   dual-corner fallback: {n_fb}   total: {n_auto + n_fb}")
+
+
+_SEG = mp.solutions.selfie_segmentation.SelfieSegmentation(model_selection=1)
+_FD = mp.solutions.face_detection.FaceDetection(model_selection=1, min_detection_confidence=0.4)
+
+if __name__ == "__main__":
+    main()
diff --git a/tooling/scripts/watermark/preview_auto.py b/tooling/scripts/watermark/preview_auto.py
new file mode 100644
index 00000000..9e67d12a
--- /dev/null
+++ b/tooling/scripts/watermark/preview_auto.py
@@ -0,0 +1,91 @@
+"""
+Render the watermark at the coordinates the placement engine chose (reads
+placements.json) and build a contact sheet for review. Auto placements use the
+ledger coords; fallbacks render dual-corner. Fallbacks are labelled so Quinn can
+see exactly where the compromise landed.
+
+Usage:
+  python3 preview_auto.py                 # all bases in the ledger
+  python3 preview_auto.py --only a,b,c
+"""
+
+from __future__ import annotations
+
+import json
+import os
+import sys
+
+from PIL import Image, ImageDraw, ImageFont
+
+from place_engine import LEDGER, STYLE
+from sources import OUT, clean_source
+from watermark_lib import WatermarkStyle, render_explicit, render_watermark, FONT_DIR
+
+PREVIEW = os.path.join(OUT, "_preview", "auto")
+CARD_W = 300
+DUAL = WatermarkStyle(mode="dual-corner", text_width_frac=0.34)
+
+
+def render_for(base: str, p: dict) -> Image.Image:
+    im = Image.open(clean_source(base)).convert("RGB")
+    if p.get("fallback"):
+        return render_watermark(im, DUAL)
+    return render_explicit(im, STYLE, (p["x"], p["y"]), int(im.width * STYLE.text_width_frac))
+
+
+def label(im, text, warn=False):
+    bar = 22
+    out = Image.new("RGB", (im.width, im.height + bar), (40, 14, 14) if warn else (18, 18, 22))
+    out.paste(im, (0, 0))
+    try:
+        f = ImageFont.truetype(os.path.join(FONT_DIR, "Audiowide-Regular.ttf"), 11)
+    except Exception:
+        f = ImageFont.load_default()
+    ImageDraw.Draw(out).text((4, im.height + 4), text, fill=(255, 120, 190), font=f)
+    return out
+
+
+def thumb(im, w=CARD_W):
+    return im.resize((w, round(im.height * w / im.width)), Image.LANCZOS)
+
+
+def grid(cards, cols=4, gap=10):
+    rows = (len(cards) + cols - 1) // cols
+    cw = max(c.width for c in cards)
+    ch = max(c.height for c in cards)
+    sheet = Image.new("RGB", (cols * cw + (cols + 1) * gap, rows * ch + (rows + 1) * gap), (10, 10, 12))
+    for i, c in enumerate(cards):
+        r, col = divmod(i, cols)
+        sheet.paste(c, (gap + col * (cw + gap), gap + r * (ch + gap)))
+    return sheet
+
+
+def main():
+    os.makedirs(PREVIEW, exist_ok=True)
+    ledger = json.load(open(LEDGER))
+    only = None
+    if "--only" in sys.argv:
+        only = sys.argv[sys.argv.index("--only") + 1].split(",")
+    bases = only or sorted(ledger)
+
+    cards = []
+    for base in bases:
+        p = ledger.get(base)
+        if not p:
+            continue
+        wm = render_for(base, p)
+        if p.get("fallback"):
+            tag = f"{base}\nFALLBACK dual-corner"
+            cards.append(label(thumb(wm), tag, warn=True))
+        else:
+            tag = f"{base}\nauto bite={p['bite_pct']}%"
+            cards.append(label(thumb(wm), tag))
+
+    sheet = grid(cards)
+    out = os.path.join(PREVIEW, "contact_sheet.jpg")
+    sheet.save(out, quality=92)
+    print("contact sheet →", out, f"({len(cards)} images)")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/tooling/scripts/watermark/sources.py b/tooling/scripts/watermark/sources.py
new file mode 100644
index 00000000..2cb52f0e
--- /dev/null
+++ b/tooling/scripts/watermark/sources.py
@@ -0,0 +1,48 @@
+"""
+Clean-source mapping for the quinn.www photo library — single source of truth
+shared by the placement engine and the batch renderer.
+
+The published named-theme set in public/photos already carries the OLD white
+watermark; those must be sourced from the un-watermarked masters. The quinn-*
+batch and the png illustrations are already clean in public/photos.
+"""
+
+from __future__ import annotations
+
+import os
+
+REPO = os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "..", ".."))
+PUB = os.path.join(REPO, "deployments/@domains/quinn.www/root/public/photos")
+ORIG = os.path.join(REPO, "users/transquinnftw/originals")
+OUT = PUB + "-watermarked"
+
+QUINN_PREFIX = "quinn-"
+PNG_BASES = {"duo-session", "specialties-solo", "destinations-travel"}
+
+
+def raster_ext(base: str) -> str:
+    return ".png" if base in PNG_BASES else ".jpeg"
+
+
+def clean_source(base: str) -> str:
+    """Clean (un-watermarked) source path for a published base name."""
+    if base in PNG_BASES:
+        return os.path.join(PUB, f"{base}.png")
+    if base.startswith(QUINN_PREFIX):
+        return os.path.join(PUB, f"{base}.jpeg")
+    master = os.path.join(ORIG, f"{base}.jpeg")
+    if os.path.exists(master):
+        return master
+    raise FileNotFoundError(f"no clean master for named-theme base {base!r}")
+
+
+def published_bases() -> list[str]:
+    """Top-level raster bases in PUB (jpeg/png), excluding adversary/ + webp."""
+    bases = []
+    for fn in os.listdir(PUB):
+        if not os.path.isfile(os.path.join(PUB, fn)):
+            continue
+        stem, ext = os.path.splitext(fn)
+        if ext.lower() in (".jpeg", ".jpg", ".png"):
+            bases.append(stem)
+    return sorted(set(bases))
diff --git a/tooling/scripts/watermark/watermark_lib.py b/tooling/scripts/watermark/watermark_lib.py
index 964433c5..82b633bf 100644
--- a/tooling/scripts/watermark/watermark_lib.py
+++ b/tooling/scripts/watermark/watermark_lib.py
@@ -251,6 +251,25 @@ def _render_tile(base: Image.Image, style: WatermarkStyle) -> Image.Image:
     return overlay
 
 
+def stamp_size(style: WatermarkStyle, target_w_px: int) -> tuple[int, int]:
+    """Width/height of the plated stamp for a given target wordmark width."""
+    s = _stamp_plated(style, target_w_px)
+    return s.width, s.height
+
+
+def render_explicit(img: Image.Image, style: WatermarkStyle, top_left: tuple[int, int],
+                    target_w_px: int) -> Image.Image:
+    """Composite one plated stamp at an explicit top-left pixel (ledger-driven)."""
+    base = img.convert("RGBA")
+    W, H = base.size
+    stamp = _stamp_plated(style, target_w_px)
+    if style.overlay_alpha < 255:
+        stamp.putalpha(stamp.getchannel("A").point(lambda v: v * style.overlay_alpha // 255))
+    overlay = Image.new("RGBA", (W, H), (0, 0, 0, 0))
+    overlay.alpha_composite(stamp, (int(top_left[0]), int(top_left[1])))
+    return Image.alpha_composite(base, overlay).convert("RGB")
+
+
 def render_watermark(img: Image.Image, style: WatermarkStyle = WatermarkStyle()) -> Image.Image:
     """Return a new RGB image with the watermark composited on. Input untouched."""
     base = img.convert("RGBA")