How do I configure a media analysis widget? Overview A media analysis widget shows AI-read results from your photos or text submissions, checked against a Check you configure — for example, counting items in a shelf photo or confirming a display is present. When to Use Use this feature when: You want an automatic read on photos or text submitted through a form — counting items, extracting a value, or scoring against a Check You don't need true computer-vision accuracy (facing recognition, object detection, SKU matching) — this feature reads images with a language model, not a vision model built for that Concepts Media Analysis Widget – Shows the results of an AI read of your media (photos or text submissions) against a Check you configure Check – What the AI is asked to do on each piece of media; choose one of five types. A Check that's already set up shows as "(configured)" in the dropdown Uniform check – A yes/no check against a single condition in the photo, such as whether something matches an expected standard Display / POSM present – A yes/no check for whether a point-of-sale display or material (POSM) is visible in the photo Count items – Counts how many of something appear in the photo — for example, how many units of a product are on a shelf; configured using one or more Values Read a value – Extracts a specific value from the photo or text, such as a price or a label reading; configured using one or more Values Quality score – Scores the photo or submission against quality criteria you describe, instead of a yes/no result or a count Value – A specific thing the AI should extract or count under a Count items or Read a value Check, given a name, a type (such as Number), and a description telling the AI what to look for; Number-type Values become ordinary columns you can sum or average elsewhere in Vantage (a KPI card, chart, or summary/pivot table) Item Reference Images – Optional reference photos you can upload so the AI knows what a correct item looks like Credits – Each media analysis job that completes successfully uses a credit; credit use is capped and tracked by your admin Media Analysis Job – The background task that reads one piece of media against a Check; jobs run asynchronously, and the dashboard refreshes automatically every 15 seconds while jobs are in progress Set Up Guide Go to a dashboard and click Add Widget, then set the Title, Apply Dashboard Filters, Widget Type (Media Analysis), and Data Source as usual Choose the media field to analyze — a photo or text column from your Data Source, such as Shelf Photo Url Under "What should the AI check?", choose a Check — Uniform check, Display / POSM present, Count items, Read a value, or Quality score For Count items or Read a value, click + Value to add one or more values — give each a name, a type (such as Number), and a description telling the AI what to look for Optionally, upload Item reference images so the AI knows what a correct item looks like Click Save & Apply Best Practices Stick to photo or text submissions — video and audio analysis exist as legacy options, but they don't produce reliable results today: video analysis only sends the model the file's URL (which it can't actually watch), and audio analysis returns a placeholder instead of a real transcript Treat results as LLM-grade, not CV-grade — there's no true object detection or facing recognition behind this; the model is reading the photo and estimating, so spot-check anything used for a compliance or scoring decision Give each Value a clear, specific description — it's literally the instruction the AI reads to decide what to extract or count, so a vague description gives vague results Avoid saving the same Check multiple times in quick succession — each save can queue new analysis jobs, and resaving repeatedly can create duplicate jobs that use up extra credits Related Links/FAQs Related pages in this book: What widget types are available in Vantage? How do I configure a calendar widget? How do I configure an AI summary widget? FAQs Is media analysis real computer vision, like object detection? No — it's a language model reading the photo (or text) against the rubric you set up. There's no true object detection, facing recognition, or SKU matching behind it, so treat results as LLM-grade, not CV-grade. Can I use it to analyze videos or audio recordings? Video and audio options exist but aren't reliable today — video analysis only sends the model the file's URL, which it can't open, and audio analysis returns a placeholder instead of a real transcript. Stick to photos and text submissions. Does every analysis use up credits? Yes — each job that completes successfully uses a credit, and credit use is capped and tracked by your admin. Version Notes Last Updated: Oct 2026