Vidopix — AI Video Intelligence

Vidopix — AI Video Intelligence

Know what works before you publish

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Vidopix helps brands, creators, and agencies test videos before launch—ads, trailers, collabs, and more. In minutes, see what works and what doesn’t with deep AI insights across 250+ languages. Identify hooks, drop-offs, and emotions. Run quick video surveys with SurveyCine, share links, and analyze authentic customer reactions. No more guesswork—Vidopix makes every video smarter
This is the 2nd launch from Vidopix — AI Video Intelligence. View more

Vidopix

Launched this week
Understand why people react the way they do in videos
Upload your video and understand how audiences are likely to react before you publish. Vidopix analyzes emotional and behavioral cues to surface engagement dips, pacing issues, and moments of confusion — helping teams fix what matters early. Built for marketers, researchers, and content teams working with video who want clarity, not guesswork
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Payment Required
Launch Team / Built With
Anima Playground
AI with an Eye for Design
Promoted

What do you think? …

Atique Bandukwala
Hey Product Hunt! 👋 Atique here, founder of Vidopix. We launched here in September 2025. Today, we're back with a major update and expanding to the US & UK. ## THE PROBLEM Our team has spent 2+ decades at Disney, Sony, ITC, GroupM, and IPG Mediabrands. We watched the same pattern repeat: → Brand creates video based on gut feeling → Publishes without testing → Spends millions on media/distribution → Video fails → Learns what went wrong AFTER the money is gone YouTube Analytics tells you what failed AFTER you publish. Facebook Insights tells you what flopped AFTER you spend. Focus groups take weeks and cost $50K+. Nobody tests videos BEFORE publishing. Until now. ## WHAT WE BUILT Vidopix is a business intelligence platform for video content. Upload any video, and in 2-3 minutes our AI tells you: ✓ Exactly where viewers will drop off (with second-level precision) ✓ Which pacing issues will cause problems ✓ What emotions your video evokes (and if they match intent) ✓ Specific fixes to make before you publish ## REAL EXAMPLE A major media network tested their documentary trailer before a $300K marketing push: → We predicted: 42% drop-off at 0:18 seconds (transition too fast) → Reality: 43% dropped at 0:19 seconds → Accuracy: 98% They fixed it, re-tested, and improved drop-off to 18%. **Impact: Saved $75K in wasted distribution.** ## THE TECH We've analyzed 4.5M+ videos across: - Media & entertainment - Advertising & marketing - Corporate communications - Social content Our AI is trained on real viewer behavior patterns across 250+ languages. **Prediction accuracy: 94%** ## WHO IT'S FOR ✓ Marketing teams testing ads before media buys ✓ Brands spending big on video distribution ✓ Content creators optimizing before launch ✓ Agencies managing client campaigns ✓ Anyone tired of publishing blind ## THE ECONOMICS **Test cost:** $1 per minute of video **Average campaign savings:** $75K+ **ROI on testing:** 2,500x on average A 30-minute video costs $30 to test. Alternative: Waste $130K on distribution that doesn't work. The math is simple. ## WHAT'S NEW SINCE SEPTEMBER ✓ 10x more training data (4.5M+ videos) ✓ Significantly improved AI reasoning ✓ 94% prediction accuracy (proven) ✓ Real case studies with measurable ROI ✓ US & UK market launch ✓ Complete product repositioning This isn't just an update—it's Vidopix 2.0. ## HOW IT WORKS 1. Upload your video (any format, up to 60 minutes) 2. AI analyzes in 2-3 minutes 3. Get instant insights on what's broken 4. Chat with Pixi (our AI) for deeper analysis 5. Fix issues before you publish 6. Spend your budget on content that actually works ## WHY DATA ANALYSIS TOOLS CATEGORY We're not just another marketing analytics tool. We're a business intelligence platform built on a database of 4.5M+ videos, providing data-driven insights that directly impact ROI. Think: Mixpanel for video, but BEFORE you publish. ## THE ASK If you're spending thousands (or millions) on video distribution: → Test one video → See what you're missing → Decide if $1/minute beats $100K+ wasted We're here all day for questions, feedback, and video testing war stories! Try it: https://vidopix.com Thanks for the support! 🚀 —Atique Founder & CEO, Vidopix P.S. We're specifically looking for feedback from: - Marketing leaders managing video budgets - Content creators testing pre-launch - Agencies running campaigns - Anyone who's wasted money on a video that flopped
Jacey

@atique_bandukwala1 This feels like the missing “pre-publish analytics” layer for video. The drop-off + emotion + pacing diagnostics sound super useful before spending on distribution. Curious: how do you validate predictions on brand-new creatives (no history), and can you benchmark against similar videos in your dataset?

Atique Bandukwala
@hijacey Appreciate this question — it’s exactly the problem we built Vidopix for. For brand-new creatives (no history), we don’t rely on channel or account data. The predictions are driven by content-level signals — structure, pacing shifts, emotional variance, narrative tension, visual/audio cues — learned from how humans react to video patterns at scale. Validation happens two ways: 1) Controlled testing where creatives are analyzed before launch and then compared with actual retention & engagement post-distribution, and 2) Blind comparisons across similar formats where the AI ranks variants — the one it flags as stronger consistently outperforms once published. Yes, benchmarking is possible — videos are compared against anonymized clusters of similar length, format, category, and intent (not copied, not trained on private brand data). Think of it less as “predicting virality” and more as removing avoidable creative blind spots before money is spent. Happy to go deeper if you’re curious — this is the fun part 🙂
Kshitij Mishra

keep making such products like these

Atique Bandukwala
@kshitij_mishra4 Thank you for the support 😊
Atique Bandukwala
👋 Founder here. Quick context: we built this after watching teams publish videos they thought would work — and then realise too late where people dropped off or disengaged. We’re curious: • For creators — what’s the hardest part of knowing if a video will work before publishing? • For teams/brands — what’s the one question you wish audience data answered instantly? Brutally honest feedback welcome. Even “this isn’t useful for me” helps.
John Spradling

Predicting performance before publishing is a hard problem. This is an interesting approach. Curious what teams most often change after seeing the insights: pacing, narrative flow, or CTA placement?