Who should use the Moderate visual content workflow?
Teams or solo builders working on security & privacy tasks who want a repeatable process instead of one-off tool experiments.
AI Workflow · Security & Privacy
Practical execution plan for moderate visual content with clear steps, mapped tools, and delivery-focused outcomes.
Deliverable outcome
Content is either published or blocked, with full traceability and user notification.
30-90 minutes
Includes setup plus initial result generation
Free to start
You can swap tools by pricing and policy requirements
Content is either published or blocked, with full traceability and user notification.
Use each step output as the input for the next stage
Step map
Instead of relying on a single generic AI model, this pipeline connects specialized tools to maximize quality. First, you'll use NucliaDB to all incoming visual content is categorized and ready for moderation checks. Then, you pass the output to Clarifai to all prohibited content is identified and flagged, with clear pass/fail per asset. Then, you pass the output to Sensity AI to manipulated or synthetic media is identified and escalated for further action. Then, you pass the output to Face++ to faces are matched to identities and verified as live, or spoof attempts are flagged. Then, you pass the output to Pega to all flagged content is reviewed by humans, with final decisions recorded and actionable. Finally, Composio is used to content is either published or blocked, with full traceability and user notification.
Ingest and classify incoming visual content
All incoming visual content is categorized and ready for moderation checks.
Detect prohibited and sensitive content
All prohibited content is identified and flagged, with clear pass/fail per asset.
Detect deepfakes and manipulated media
Manipulated or synthetic media is identified and escalated for further action.
Perform facial recognition and liveness detection
Faces are matched to identities and verified as live, or spoof attempts are flagged.
Escalate and review flagged content
All flagged content is reviewed by humans, with final decisions recorded and actionable.
Deliver moderation results and enforce actions
Content is either published or blocked, with full traceability and user notification.
Collect all visual assets (images, videos, frames) from uploads, APIs, or batch imports. Use automated classifiers to tag content by type (e.g., photo, video, meme) and source (user-generated, third-party, internal). This ensures downstream moderation rules apply correctly.
Why NucliaDB: NucliaDB provides automated document ingestion and indexing with semantic search over multi-modal documents, which directly supports content ingestion and classification of visual content.
Apply AI models to scan each image/frame for policy violations: nudity, violence, hate symbols, gore, or custom blacklists. Use a combination of general-purpose NSFW detectors (e.g., NSFW JS, Google Vision SafeSearch) and fine-tuned models for specific categories. Flag any matches for human review or automatic rejection.
Why Clarifai: Clarifai provides image recognition, object detection, and text classification, which are directly applicable to detecting prohibited and sensitive content.
Analyze visual content for signs of AI-generated or manipulated imagery using deepfake detection models (e.g., Deepware, Microsoft Video Authenticator). Check for inconsistencies in facial landmarks, lighting, and metadata (e.g., EXIF). Flag suspicious assets for deeper forensic review.
Why Sensity AI: Sensity AI specializes in deepfake detection, media authentication, and image forensics, directly matching the needs of this step.
If the content includes faces (e.g., profile photos, verification selfies), run facial recognition to match against user profiles or watchlists. Simultaneously, apply liveness detection (e.g., blink detection, texture analysis) to confirm the face is from a live person, not a spoof (photo, video, mask). This step is critical for identity verification workflows.
Why Face++: Face++ provides facial identity verification, liveness detection, and skeletal tracking, directly covering all needs of this step.
All content that fails automated checks (prohibited content, deepfake suspicion, spoof attempt) is sent to a human moderation queue. Provide moderators with context (scores, model outputs, original asset) and clear action options: approve, reject, or escalate. Use a dashboard (e.g., Label Studio, custom tool) to track decisions and ensure audit trails.
Why Pega: Pega offers workflow automation and case management capabilities, which are essential for human moderation dashboards and escalation processes.
Based on final decisions, execute actions: allow content to pass, block it, or trigger downstream processes (e.g., account suspension, legal reporting). Return results to the originating system via webhook or API response. Optionally, update user-facing status (e.g., 'Under review', 'Rejected').
Why Composio: Composio connects AI agents to external SaaS applications and manages OAuth authentication, enabling action execution and notification delivery.
§ Before you start
Teams or solo builders working on security & privacy tasks who want a repeatable process instead of one-off tool experiments.
No. Start with the top pick for each step, then replace tools only if they do not fit your pricing, compliance, or output needs.
Open the mapped task page and compare top options side by side. Prioritize output quality, integration fit, and predictable cost before scaling.
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