Automate Brand-Safety and Compliance Review for Video

Someone has to watch the video before it goes live. A brand paying for a creator campaign needs to know the video is safe to put its name on. A platform needs to catch harmful uploads before they're public. A regulated business needs proof that every ad includes the required disclosures.

Today that "someone" is usually a person watching at 1.5x speed with a checklist. It's slow, it's expensive, and it gets less reliable with every hour of footage.

The Clipperia Video Intelligence API does the first pass for you. It reviews every video against your rules and returns a structured report, with every issue pinned to the moment it happens. Your reviewers stop watching everything and start reviewing only what was flagged.

What you can check

You write the rules in plain language, the same way you'd brief a human reviewer. Common checks include:

Brand safety

• Profanity, explicit language or sexual content
• Violence, weapons, drugs or alcohol
• Hate speech, harassment or slurs
• Controversial or sensitive topics your brand wants to avoid

Brand and campaign requirements

• Was the sponsor mentioned, and how many times?
• Was the promo code or link said correctly?
• Were competitor brands mentioned or shown?
• Did the creator follow the talking points in the brief?

Disclosures and compliance

• Is there a clear sponsorship disclosure, such as "#ad" or "paid partnership", and where?
• Are required disclaimers present in financial, health or legal content?
• Were any claims made that your policy doesn't allow, like guaranteed results or medical promises?

Platform moderation

• Content that's unsafe to publish
• Content that isn't appropriate for younger audiences
• Spam, scams or misleading content

How it works

Step 1: Write your review rules as a question

Turn your checklist into a question, and describe the fields you want back. For example:

"Review this video for our brand-safety policy. Return each issue found with a category (profanity, violence, alcohol, sensitive topic, competitor mention), severity (low, medium, high), a short description, and the timestamp. Also tell us whether a sponsorship disclosure was made and when."

Step 2: Send each video once

Send videos as they come in, whether that's creator drafts, new user uploads or ad cuts. You don't run any video infrastructure, and you're notified when each review is ready.

Step 3: Use the report to route the video

Every video comes back with the same structured report, so you can automate the decision:

• No issues → approve automatically, or send to a light spot-check
• Low-severity issues → send to a reviewer with the flagged moments listed
• High-severity issues → block, or escalate to your trust and safety team

Because every flag has a timestamp, a reviewer can jump straight to each moment and make a decision in a couple of minutes instead of watching the whole video.

Step 4: Keep the record

Store each report with the video. When a brand, partner or regulator asks how a video was reviewed, you have a record of what was checked and what was found, with timestamps.

Why automate the first pass

• Speed. Campaign approvals and upload moderation stop waiting on someone's free time.
• Consistency. The same rules apply to every video, including the last one at the end of a long day.
• Coverage. You can review everything, not a random sample.
• Focus. Your reviewers' judgment goes to the gray areas, not to watching hours of footage that has no issues.

Change the rules without reprocessing

Policies change. A brand adds a new competitor to avoid, or a regulator updates its disclosure rules.

Each video is processed once when it arrives. After that, checking it against a new rule is just another question. You can re-check a whole campaign's worth of videos against an updated policy without re-uploading or reprocessing anything.

Speech vs. what's on screen

Many checks can be answered from what's gathered when a video is first uploaded, like what's said, what's discussed and what's mentioned. These standard analyses are the fast, inexpensive default.

Some checks need a closer look at specific details on screen. For example: "is the disclosure shown as on-screen text?" or "does a competitor's logo appear?" For those, use a visual analysis. It costs more, so many teams run it only on videos that pass the standard check, or only for the specific rules that need it.

Where people still matter

Automated review is a first pass, not the final decision. The API finds and describes what's in a video. It doesn't make legal judgments, and it doesn't fact-check claims. Keep a person responsible for final approval on anything high-stakes. Use the reports so that person spends minutes per video, not the whole runtime.

The API also doesn't identify people by their faces. If your rules depend on who appears in a video, base them on names that are spoken or shown on screen.

Who this is for

• Influencer marketing platforms and agencies approving creator content before payout
• Brands checking sponsored content and ad placements
• UGC platforms and communities moderating uploads before they go public
• Regulated businesses in finance, health and legal checking video marketing for required disclosures
• Ad networks screening video creative at volume

Get started

The Video Intelligence API is opening to the waitlist first. When you join, tell us what you review videos for and how many you handle. That helps us decide who gets access first.

Moderating video for creators instead? Clipperia's profanity censor cleans up clips automatically before you post them.