Industries · AdTech
Brand-safety data for every format
Profanity and unsafe content flagged at the frame and the second, across on-screen text, speech, music, and images, plus IAB-aligned classifications that keep ads out of the wrong places.
The problem
What makes adtech data hard
Every modality at once
Offensive content hides in visuals, captions, dialogue, and background lyrics — often in the same clip.
Timestamp precision
Brands need to know exactly when unsafe content appears, down to the frame and the second.
False flags cost money
Over-flagging blocks good inventory; under-flagging damages the brand. Both show up on the bottom line.
How MLtwist helps
One pipeline, built for this data
Our platform prepares and routes the data; our team, yours, or both label it. Every version ships with a Data ID Card.
- AI pre-labeling, human review
- Models pre-label every clip, and our reviewers clean, correct, and QA the results.
- Frame-level flagging
- Unsafe content is marked with its exact timestamp and modality.
- IAB-aligned taxonomy
- Labels map to the industry's brand-safety and suitability guidelines.
- Any source
- MP4 files and direct URLs from video platforms, ingested and normalized automatically.
Case studies
AdTech programs we've delivered
AdTech company · AdTech
How AdTech Uses AI and MLtwist to Apply Brand Safety Classifications
AdTech company · AdTech
MLtwist Empowers AdTech with AI-Powered Content Moderation for Brand Safety
Related work
Bring us your adtech data
Tell us the data type, volume, and timeline. We'll scope it with our team, yours, or both — and deliver it versioned, in your format.
Also available through Carahsoft and Google Cloud Marketplace.