Summary: AdRadar is the media-buying loop: a creative image (and optional video) becomes readable copy, a voiceover transcript, a fatigue flag from spend and age, and a CLIP index for lookalikes. You do not run OCR, Whisper, a scoring spreadsheet, and Pinecone as four products. You declare Ads. pip install pixeltable.
The Product#
- Ingest
creative_imagewith optionalcreative_video - Store spend, impressions, conversions,
active_days - Read on-image copy with Gemini — not a fake OCR product
- Flag creatives that have been live too long with a weak conversion rate
- Drop a competitor screenshot; return nearest ads
SKU shop-the-look is SnapCatalog. This post is the same CLIP-on-image index with campaign telemetry on the row.
The Stitch You Delete#
A folder of exports from the ad account. A VLM batch for copy. Whisper for video ads. A sheet that divides conversions by impressions. Embeddings in a sidecar keyed by ad_id. Pixeltable is the creative row those joints were reconciling in ops.
The Receipt#
fatigue_risk is arithmetic on columns you already store — days live and conversion rate — not a trained fatigue model we pretend to ship. Gemini reads the pixels for copy. CLIP on the image is the copycat path, same embedding= form as SnapCatalog. Same file on Cloud: db → schema → service.
What This Is Not#
Not Meta Ads Manager. Not a bid optimizer. Spend truth stays in the ad account. Not an OCR vendor. Not PixelSearch as a hosted consumer UI.
People Also Ask#
Image-only ads? Leave creative_video null. Voiceover is empty; the image path still runs.
Why not a second MiniLM index on copy? You can add one. This receipt keeps CLIP on the pixels so lookalikes do not depend on OCR quality.
How do I go to Cloud? Same app.py. PIXELTABLE_API_KEY, pxt://org:db, then pxt db update → pxt schema update → pxt service update.
Is this an AI automation workflow? Yes. Insert the creative; copy, fatigue arithmetic, and CLIP run as columns. The category is AI automation workflow.
Score the Row, Search the Pixels#
Declare the creative. Apply the file. Insert the JPEG. Query HIGH and lookalikes. Keep the catalog. Delete the tagging farm.
- Pixeltable on GitHub:
pip install pixeltable - ReelForge — podcast chapters
- MedDossier — clinical intake row
- LectureSync — slides + lecture video
- SnapCatalog — shop-the-look
- Pixeltable documentation
