Getting started with moderation

This guide covers both ways to moderate a ready media asset, in the FastPix dashboard and with the API, and how to read the response so you can allow, review, or block the content. For what moderation detects and how the scores work, see Content moderation.

Note: You can generate AI features only for existing media. Upload and process your video first, then run moderation on the ready media.

Prerequisites

• A FastPix account with an active workspace (Activate your account)
• A ready video asset in your workspace
• Your Access Token ID and Secret Key if you use the API

Run content moderation from the FastPix dashboard

To run moderation without calling the API:

1. Open the media item: From the FastPix dashboard, go to Media > [your media item] and open the Media Details page.

2. Open the moderation tab: On the Media Details page, click the Moderation tab to view the moderation controls and history.

3. Run the check: Click Generate to start moderation on the media.

4. View the results: When moderation completes, the detected categories and their confidence scores appear in the tab.

5. Take action: To block playback automatically, update the media accessPolicy or playback rules when a high-confidence detection appears. For manual review, forward the flagged categories to your review queue or ticketing system.

Run content moderation with the API

Run moderation and fetch the results programmatically with the In-Video AI API. The video moderation API is asynchronous, so you trigger it, wait for the webhook or poll, then read the result. Both endpoints use Basic authentication with your Access Token ID and Secret Key.

Trigger moderation

Send a POST to the Moderate video content and detect profanity endpoint with the mediaId of a ready asset.

curl --request POST \
  --url https://api.fastpix.com/v1/ai/{mediaId}/moderation \
  --user '{Access_Token}:{Secret_Key}'

The response confirms that the job started:

{
  "success": true,
  "data": {
    "id": "c695988b-ff84-42ae-bb21-10f284fedb0e"
  }
}

Moderation configuration

The moderation API accepts an optional JSON configuration body for controlling audio and video moderation. Send it as the request body on the trigger POST.

{
  "modalities": ["video", "audio"],
  "language_code": "te",
  "categories": [
    "violence",
    "sexual",
    "profanity",
    "threats",
    "harassment",
    "hate_speech"
  ],
  "thresholds": {
    "sexual": 0.4,
    "violence": 0.4,
    "profanity": 0.3,
    "threats": 0.3,
    "harassment": 0.3,
    "hate_speech": 0.3
  },
  "sampling": {
    "interval_seconds": 5
  }
}

Parameters

Supported categories

For the categories moderation can flag and what each one covers, see Moderation categories.

Behavior

When both modalities are selected:

• Video moderation analyzes sampled video frames.
• Audio moderation transcribes the audio in the original language.
• Audio timestamps are mapped back to the source transcript.
• Video and audio results are combined into a single moderation response.

The configuration body is optional. If you omit it, the API applies these defaults:

• Modalities: detected automatically from the media. A video that has an audio track is moderated on both tracks, an audio-only asset on audio, and a video-only asset on video.
• Categories: all supported categories.
• Language code: detected automatically from the audio.
• Sampling interval: 3 seconds.

Wait for the result

Moderation runs in the background. Subscribe to the video.media.ai.moderation.ready webhook to be notified when the analysis completes, or poll the get-results endpoint.

Get the moderation result

Send a GET to the Get video moderation results endpoint.

curl --request GET \
  --url https://api.fastpix.com/v1/ai/{mediaId}/moderation \
  --user '{Access_Token}:{Secret_Key}'

Understand the moderation response

The response contains a moderation object that summarizes the analysis and lists every flagged segment with its time range. A sample response for an unsafe video:

{
  "moderation": {
    "verdict": "unsafe",
    "modalities": ["video", "audio"],
    "scores": {
      "threats": 0.5,
      "violence": 0.8661,
      "profanity": 0.5
    },
    "segments": [
      { "modality": "audio", "start": 0.1, "end": 12.74, "riskScore": 0.3, "categories": { "violence": 0.3, "threats": 0.3 } },
      { "modality": "video", "start": 54, "end": 81, "riskScore": 0.8661, "categories": { "violence": 0.8661 } },
      { "modality": "video", "start": 81, "end": 108, "riskScore": 0.5197, "categories": { "violence": 0.5197 } },
      { "modality": "audio", "start": 88.19, "end": 98.53, "riskScore": 0.5, "categories": { "profanity": 0.5 } },
      { "modality": "audio", "start": 126.82, "end": 140.19, "riskScore": 0.3, "categories": { "profanity": 0.3 } },
      { "modality": "audio", "start": 140.19, "end": 153.6, "riskScore": 0.5, "categories": { "violence": 0.5, "threats": 0.5 } },
      { "modality": "audio", "start": 153.6, "end": 169.12, "riskScore": 0.5, "categories": { "profanity": 0.5 } },
      { "modality": "video", "start": 270, "end": 297, "riskScore": 0.7656, "categories": { "violence": 0.7656 } },
      { "modality": "audio", "start": 308.64, "end": 318.88, "riskScore": 0.5, "categories": { "profanity": 0.5, "threats": 0.5 } },
      { "modality": "audio", "start": 318.88, "end": 335.14, "riskScore": 0.5, "categories": { "threats": 0.5 } },
      { "modality": "audio", "start": 404.23, "end": 422.21, "riskScore": 0.4, "categories": { "violence": 0.4, "threats": 0.4 } },
      { "modality": "audio", "start": 476.87, "end": 497.31, "riskScore": 0.5, "categories": { "profanity": 0.5 } }
    ]
  }
}

All scores are numbers from 0 to 1, where a higher value means stronger confidence that the category is present, not that the content is more severe.

Read the response at two levels:

• Top level, for a quick decision. verdict and scores summarize the whole media. In this example, violence reaches 0.8661, so the media is marked unsafe. The top-level scores reflect the strongest finding for each category across all segments.
• Segment level, to act precisely. Each entry in segments gives the exact start and end (in seconds) of a flagged moment, its modality, and the categories that triggered it. Use the timestamps to review, redact, or clip just that moment instead of the whole file.

Compare scores and each segment’s riskScore against the thresholds you set, then apply your content policy. For more context, see the blog post AI content moderation using NSFW and profanity filters.

Act on the result

Map the scores to an action that matches your content policy:

• Below your review threshold: allow the content to publish.
• In your review band: set the media to private and send it to a human review queue.
• Above your automatic-action threshold: restrict playback by updating the media accessPolicy, and alert your trust and safety team.

Because each segment includes its start and end time, you can target a fix at the exact moment instead of the whole video, for example beep out profanity by replacing the audio track or cut a flagged moment by removing unwanted video segments.

To wire these decisions into an end-to-end flow, see Gate uploads before publishing.

Limits and considerations

• Moderation runs on a ready video, so wait until the media has finished processing before you run it.
• Sampling produces the strongest results on short-form video. Evaluate accuracy on your own content before relying on it for long videos.
• Set a confidence threshold that matches your platform’s tolerance, and sample your own catalog before fixing the values.
• Audio moderation, including profanity, runs on the transcript, so it is limited to the supported audio moderation languages.

What’s next

Once moderation returns a finding, act on the flagged content:

• Beep out or replace profane audio: Replace a video’s audio track or Overlay audio on a video timeline.
• Cut a flagged moment: Clip and trim videos or Remove unwanted video segments.
• Rebuild a clean version: Merge and stitch videos.