Explicit content in a UGC video upload
Detected at the frame level. Video held before going live.
Explicit content flagged at 1:23
AI video moderation for user-generated content
Moderate video content frame by frame, and by audio track. Lasso extracts frames at customizable intervals and transcribes the audio separately.
A threat spoken in a video post
Audio transcribed and moderated as text. Video removed automatically.
Threat detected in audioInappropriate scene in a live broadcast
Detected frame by frame in real time. Stream interrupted before most viewers see it.
Flagged in real timeDeepfake video uploaded as user content
AI-generated face swap detected at the frame level. Flagged before publication.
Deepfake detected
Lasso's four-layer video moderation pipeline
1Frame sampling & ML
Automated screenshots extracted from uploaded video, each frame scanned against 50+ content categories.
High-confidence decisions made at scale. The same ML pipeline that powers Lasso's image moderation.
See Lasso in action
Explicit region — frame 0823
Frame Classification
Classification complete
Classification
Explicit nudityNSFW
Frame sampled
Frame 823 of 5,400SAMPLED
Timestamp
Violation at 1:23TIMESTAMP
Detection confidence97%
2Custom rules
Your platform rules applied to every flagged frame.
Set the violence threshold, nudity confidence level, and custom content categories from the dashboard. No code required.
See Lasso in actionLayer 1 Output
1Explicit nudity: 97%
2Audience: public feed
3Uploader age unverified
Custom Rules
BlockExplicit content on public uploads
Explicit nudity
Graphic violence
Sexual content
Self-harm imagery
Blocked
Video held before going live
3AI Moderator
Frames flagged with low confidence reach the AI Moderator.
The AI Moderator weighs context per frame, so news footage reads differently from gratuitous violence and art reads differently from explicit material. It resolves most flagged frames without human review.
See Lasso in action
Face manipulation detected
AI Moderator
Analyzing
Frame analysis
Talking-head clip, single subject, indoor vlog
Anomaly detected
Facial texture too smooth, lighting mismatch at jawline
Pattern recognized
Face-swap artifacts around hairline, consistent across frames
Classification
Deepfake — AI-generated face manipulation
Escalated
Confidence below auto-action threshold
4Human review
Flagged frames queued for human review with surrounding context.
Moderators see what came before and after, with timestamp navigation and AI confidence scores. Every decision retrains the model.
See Lasso in actionQueued for review
AI Moderator reasoning
Facial texture and jawline blending suggest a face-swap. Lighting inconsistent across frames — probable deepfake.
Human Review1 of 3
Detection data
Face manipulation: 74% | Frames affected: 0:00–0:08
AI assessment
Probable deepfake — jawline blending inconsistent with camera motion across frames
AI confidence
Face manipulation74%
Below auto-action threshold (90%)
This decision will train the AI for future similar content
Four capabilities included in Lasso's AI video moderation
Video sampled into frames automatically. Each frame analyzed for nudity, violence, hate symbols, drugs, weapons, and 50+ other content categories. Exact timestamp of every violation logged.
Sampled frames5,400 frames
1:21
1:22
1:22
Flagged1:23
1:24
1:24
Detected categories
Explicit nudity97%
Violence8%
Weapons3%
Drugs2%
Hate symbols1%
Violation logged
00:01:23
Frame 823 of 5,400
Video audio transcribed automatically. Toxic speech, hate speech, PII, and threats detected in what was said, not just what was shown.
Lasso samples and analyzes frames as the broadcast happens, flagging violating content within seconds and notifying moderators in real time.
A dedicated review queue for flagged video content. Moderators see the flagged frame, what came before and after, the timestamp, and the AI's assessment. No separate tools required.
Sampled frames5,400 frames
1:21
1:22
1:22
Flagged1:23
1:24
1:24
Detected categories
Explicit nudity97%
Violence8%
Weapons3%
Drugs2%
Hate symbols1%
Violation logged
00:01:23
Frame 823 of 5,400
Lasso: next-gen AI content moderation
99.9%
Runs on autopilot. Every decision sharpens it.
Three layers of AI clear the volume, enforce your rules, and surface the grey areas. Your team sees only what needs a human, and each call they make trains the next pass.
Keep users safe without driving them away.
Customizable moderation that lets you find the right balance between safety and user experience. So you protect your community without suppressing the culture that makes it worth joining.
Complexity removed from content moderation.
One API. Clear dashboards. A moderation pipeline built around one-click actions and the right context, right where you need it.
★★★★★
4.9
Highest rated in content moderation on G2.
Every industry has its video risks. Lasso catches them.
Social platforms
UGC video at scale, where one violating clip can spread across hundreds of profiles.
- Explicit content spliced into otherwise innocent-looking video compilations.
- Users narrating hate speech over gameplay footage or reaction videos.
- Video spam accounts uploading the same violating clip across hundreds of profiles.
Adult entertainment
Frame-level age and consent checks, down to the individual clip.
- Video content reclassified mid-upload to dodge category-based filters.
- Performers appearing in content they did not consent to: face recognition required at the frame level.
- Regulators requesting proof that age verification was applied to video, not just profile photos.
Events & live streaming
Real-time moderation for live broadcasts at peak traffic.
- Hate symbols and offensive gestures shown on-camera during live broadcasts.
- Peak-traffic events where moderation queues overflow and violations go unreviewed for hours.
FAQs
AI video moderation, answered
Lasso automates roughly 99.9% of moderation decisions across its four-layer pipeline, with only genuine edge cases routed to human reviewers. Each frame is scored against 50+ content categories, and uncertain frames pass to the AI Moderator before any escalation. Confidence scores accompany every decision, so your team always sees how a call was reached.
Yes. Lasso analyzes video frame by frame, so an AI-generated face swap is caught at the frame level and flagged before publication. The same per-frame analysis that surfaces nudity and violence also picks up manipulated faces. Reviewers can jump to the exact timestamp of the flagged frame for context.
Manual review forces a moderator to watch every minute of every upload, which does not scale as volume grows. Lasso analyzes frames and the transcribed audio track automatically, automating around 99.9% of decisions and sending only the unclear cases to your team. Reviewers then act with full context, including the surrounding frames, the timestamp, and the AI's reasoning.
Lasso is a platform with an API and a dashboard, so you connect your video sources through one API and configure rules in the dashboard without writing code. Frame analysis and audio transcription run through the same four-layer pipeline and feed a single review queue. You can set violence thresholds, nudity confidence levels, and custom content categories per platform.
AI video moderation uses machine learning to analyze video content for harmful material including nudity, violence, hate symbols, and more. Frames are extracted and classified automatically. The audio track is transcribed and moderated separately. Platforms use it to moderate user-generated video at scale without proportional staffing increases.
Lasso extracts frames from uploaded video automatically. Each frame is classified for harmful content. Audio is transcribed and moderated as text. Both run through four layers: ML classification, custom rules, AI Moderator review, and human escalation for edge cases.
Yes. Live streams are processed in real time as they broadcast. Frames are sampled and analyzed as they happen. Explicit content, violence, and policy violations are detected within seconds of appearing. Same content coverage as stored video.
Yes. Video moderation in Lasso covers two tracks. Frames are extracted and analyzed for visual violations. The audio track is transcribed and moderated for toxic speech, threats, hate speech, and PII. Both run through the same pipeline and the same review queue.
Live stream frames are analyzed in real time as they broadcast. Stored video is processed automatically after submission. Time to complete analysis depends on length and content density. Contact Lasso for specifications relevant to your video volume and format.
See what's hiding in your video
Lasso moderates user-generated video frame by frame and transcribes every audio track, catching what image-only filters miss. One pipeline, one API.
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Lasso Moderation
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