A public methodology, two credentialed reviewers, 2,204 titles scored on a 0-to-200 rubric. We integrate with platforms, publishers, AI engines, and creators through embeddable score chips, structured data, and direct licensing paths.
Every TVI partnership starts with the same thing every viewer touches: the rubric, the reviewers, and the scoreset. None of it is hidden. All of it is reproducible.
Methodology: public at tvintelligentsia.com/methodology/, downloadable PDF, screenshot-ready Formula Card. Reviewers: Jordan Robinson, MD, MPH and Cordelia Witty, EdS., NCSP, both named on every title page with Person schema and hasCredential. llms.txt: published at tvintelligentsia.com/llms.txt for AI-engine grounding.
The fastest path to integration. Paste three lines, render a live, score-stamped chip for any title in the database. Self-contained, ~4.6KB, system fonts, renders in <100ms. The chip is a link back to the canonical title page on TVI.
Every embed fires a Plausible event tagged with referrer domain, so we both get attribution data without anyone setting up GA pixels or sharing UTMs. Browse and copy embed codes at tvintelligentsia.com/embed/.
The TVI rubric is a structured first-party measurement of media-quality. For platforms and AI engines that need richer data than a chip embed, we offer two licensed paths.
Per-title JSON with the full breakdown (IQ Score, three sub-dimensions, tier, kids-specific SEL score, age recommendation, methodology version). Refreshed weekly. Suitable for streaming-platform "Quality Score" surfaces, recommendation algorithm features, and editorial CMS integrations.
Structured data for LLM grounding (ChatGPT, Perplexity, Claude, Gemini, on-platform AI features). The methodology page and llms.txt give your model citation-grade source material for any "is X worth watching" or "what should I watch" prompt. Engineering teams building on the Anthropic or OpenAI APIs can request a curated context-pack tuned for media-quality queries.
Both paths are licensed. Pricing is per-impression for embed-style surfaces and a flat per-quarter license for direct data integration. Contact us for terms.
We co-publish with editorial partners on stories where a public rubric does work that uncredentialed opinion cannot.
Integrate the IQ Score into title detail pages or quality-curation surfaces. Optional methodology deep-link for the credibility check. Licensed direct-data feed.
Discuss integration →llms.txt + methodology page + structured per-title data give your model a defensible source for any "is X worth watching" prompt. Curated context-pack available.
View llms.txt →We bring scored data, methodology citation, and credentialed-reviewer voice. You bring the audience and the editorial frame. Custom score analyses on request.
Pitch a collaboration →Free. Three lines of iframe code. No auth. No tracking pixel. Drop a score into a post, get a live link back to the title page, every render fires an attribution event tagged with your domain.
Get an embed code →Specifying the boundaries makes the rest of the partnership easier to scope.
Tell us what surface you're building and what your timeline looks like. We answer within two business days. For creators using the free embed widget, no contact is needed, just paste the iframe.
Press and journalist inquiries: same address, subject line "Press." Methodology questions: see tvintelligentsia.com/methodology/ first; the rubric is public.