Every frame, already tagged.
A two-pass Claude vision pipeline auto-detects products in every UGC photo and video frame, maps them to your SKUs, and places hotspots at the right second. Above 80% confidence auto-accepts; below queues for a 30-second human review.
- Two-pass vision: detect → recognise
- Above 80% auto-accepts; below queues for review
- Cross-channel SKU map (IG handle ↔ Shopify SKU)
- Hotspot timing for video — right product, right second
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Auto-accept · ≥ 80%
Linen blazer · Sand · 0:08–0:14
Every UGC frame, already tagged.
Two-pass Claude vision. Above 80% confidence auto-accepts; below queues for a 30-second review.
- 80%auto-accept rate
- $0.001per asset
- +27%hotspot CTR
Four steps. Ingest to hotspot.
The tagger runs on every asset in your DAM continuously. Re-tag when you change SKUs; the hotspot timeline updates in place — no re-import, no re-publish.
Step 1
Ingest the asset
From Instagram, TikTok, YouTube, a hashtag campaign, the DAM, or a creator upload. Same pipeline for image and video.
Step 2
Pass 1 · Detect
Fast vision model finds candidate products + bounding boxes inside the frame.
Step 3
Pass 2 · Recognise
High-precision pass verifies candidates against your SKU set. Confidence score per match.
Cross-channel SKU mapStep 4
Accept or queue
Above 80% auto-accepts and places a hotspot. Below queues for human review in the DAM.
Three things to know before you turn the threshold down.
Two-pass, not one-pass
Detect-then-recognise is slower than a single pass but catches multiple products per frame and aligns confidence scores with your SKU set.
Confidence threshold is yours
Default 80% auto-accept. Bump it to 90% for high-AOV stores. Lower it for catalogue exploration. Live setting, no re-run needed.
Hotspot timing on video
For video, the tagger computes the timestamp range where each product appears so the hotspot fires at the right second.
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