Safety

Analyze video for visual safety concerns across extracted frames

Upload a video file (mp4, webm, quicktime, avi — max 100MB, max 10 min). Extracts key frames at even intervals and runs vision analysis on each frame. Returns per-frame results, flagged timestamps, and an aggregated overall risk score. Ideal for moderating uploaded video content, screen recordings, and video messages.

post/api/v1/safety/video

Request

  • Base URL: https://api.tuteliq.ai
  • URL: https://api.tuteliq.ai/api/v1/safety/video
  • Auth: one of:
    • HTTP bearer
    • API key in header x-api-key

Response

Default Response

file_idstring
frames_analyzednumber
duration_secondsnumber
categoriesstring[]

Visual harm categories across every flagged frame, deduped.

overall_risk_scorenumber
overall_severity'none' | 'low' | 'medium' | 'high' | 'critical'
detectedboolean

A concern was observed at ANY severity, including monitor-only cases. For production branching prefer recommended_action.

confidencenumber

Confidence in the overall verdict (0-1), from the frame that drove it.

recommended_action'none' | 'monitor' | 'flag_for_review' | 'block' | 'immediate_intervention'

Routing key, weakest to strongest: none, monitor, flag_for_review, block, immediate_intervention. Safe to switch on. A video whose frames could not be decoded returns flag_for_review, never none.

action_detailstring

Human-readable expansion of recommended_action for a moderator UI. Free text: do not branch on it.

rationalestring

Why this verdict was reached. Built from category and severity labels only; never contains the frame descriptions.

credits_usednumber

Number of credits consumed by this request

external_idstring
incident_moderation_enabledstring

Per-call override of account incident logging: "true" forces persistence, "false" suppresses it. Omit for account default.

customer_idstring
metadataobject

Echo of the metadata you provided in the request

Changes

No recorded changes to this operation across all 1 revision of this API.