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Protect your community at scale. AI moderation agents instantly filter toxic text, ban spammers, and block NSFW images 24/7.
An AI content moderation agent reviews every piece of user-generated content — text, images, video frames, audio — against your policy, decides the confident cases automatically (approve the clean, remove the clearly violating) and queues the rest for a human with the reason and the evidence highlighted. In a marketplace it also checks listings; in a community it handles reports and appeals; on a live stream it scores frames and messages in under a second and can mute or blur on its own. The model reads; the policy decides; the moderator handles the edge cases — which is also where moderator well-being improves, because the worst content is decided by the model, not read by a person.
If two of these are yours, the processes below are where to start. Free audit — or read on.
What we build
from $247/ month
3 ready content moderation workflows on n8n — set up, hosted and maintained for you. You keep the JSON.
from $2,000one-time
Built for your systems and rules on Claude and n8n. Live in 2–4 weeks with documentation and a walkthrough; maintenance optional from $99/month.
95%
of Listings Reviewed Automatically — AI Content Moderation Agent for an Online Marketplace
What you get
The 3 outcomes teams name first — measured on the process, not promised in a deck.
Instantly block inappropriate content before it is seen publicly
Drastically reduce the psychological toll on human review teams
Ensure brand-safe environments for advertisers
Real deployments
Real outcomes from real builds — not marketing copy.
All case studiesof Listings Reviewed Automatically
How a peer-to-peer marketplace used an AI content moderation agent to review 2M+ monthly listings—catching prohibited items, scam patterns, and policy violations with 98% accuracy.
Read deployment →90%of Toxic Chat Handled Automatically
How a multiplayer gaming platform with 500K monthly users deployed an AI content moderation agent to automatically handle 90% of toxic chat while cutting false positives by 60%.
Read deployment →How it works
3 steps, none of them yours to code.
Use cases
Problem
User-generated platforms face a flood of toxic content. Human moderators can't review every post before it's seen by other users.
Solution
The AI agent intercepts content at submission. Clean content passes instantly. Toxic content is blocked. Borderline content enters a human review queue.
What you get
How to get started
Tools: OpenAI Moderation API, Hive Moderation, Sightengine
Problem
Visual content is harder to moderate than text. NSFW or violent images can go viral before human moderators catch them.
Solution
The AI scans every uploaded image and video frame in real time, classifying content against your policies. Violations are blocked or blurred; clean content passes.
What you get
How to get started
Tools: Sightengine, Hive Moderation, ActiveFence
Problem
Regulators and advertisers increasingly require transparency about content moderation practices. Manual reporting from moderation logs is error-prone and time-consuming.
Solution
The AI agent aggregates moderation actions across your platform, categorizes them by policy type and outcome, tracks appeals and reversals, and generates compliance reports meeting regulatory standards (DSA, COPPA, etc.).
What you get
How to get started
Tools: ActiveFence, L1ght, Hive Moderation
Problem
Content moderation appeals pile up. Human reviewers spend hours re-evaluating decisions, many of which are straightforward reversals due to false positives or policy updates.
Solution
The AI agent re-examines the flagged content with fresh context: updated policies, user history, appeal explanation, and community standards. Straightforward cases are resolved automatically; ambiguous cases go to human reviewers with AI recommendations.
What you get
How to get started
Tools: ActiveFence, Hive Moderation, OpenAI Moderation API
Problem
Content policies become outdated as language evolves. New slang, coded language, and evasion tactics bypass existing rules. Manual policy updates are always reactive.
Solution
The AI agent continuously analyzes moderated content patterns, identifies emerging trends (new hate speech terms, viral harmful challenges, evasion tactics), and recommends specific policy updates with evidence and examples.
What you get
How to get started
Tools: L1ght, ActiveFence, Sightengine
Problem
Live streams generate thousands of hours of unreviewed content daily. Human moderators cannot watch every stream simultaneously, and policy violations during live broadcasts—hate speech, nudity, self-harm—can go undetected for minutes or hours, causing brand damage, regulatory fines, and real harm to viewers before anyone intervenes.
Solution
The AI agent processes video frames and audio transcription in parallel, running multi-modal classifiers that detect nudity, violence, hate speech, and other policy violations within 2–5 seconds. When a violation is detected, it can auto-mute audio, blur the video feed, issue an on-screen warning, or terminate the stream entirely based on severity—while logging the incident for human review.
What you get
How to get started
Tools: Hive Moderation, Amazon Rekognition, Azure Content Safety
Problem
Platforms receiving tens of thousands of daily uploads cannot manually review every piece of user-generated content. Prohibited items (counterfeit goods, unsafe products, scam listings), offensive imagery, and spam slip through, degrading trust and exposing the platform to legal liability. Manual review queues create 12–48 hour backlogs, allowing harmful content to be live for hours.
Solution
The AI agent screens every upload at submission time, running image classifiers, OCR text extraction, and NLP analysis in a single pipeline. Clean content is auto-approved and published immediately. Clearly violating content is auto-rejected with a reason code. Borderline content is routed to a prioritized human review queue with the agent's confidence score and violation rationale, cutting reviewer decision time in half.
What you get
How to get started
Tools: Hive Moderation, Spectrum Labs, Besedo
Workflows we build
Each blueprint shows the trigger, the steps with the n8n nodes named, the guardrails and an importable template — and what it costs to have us run it for you.
All blueprints| Workflow | Department | Steps | Managed | Custom build |
|---|---|---|---|---|
| AI Social ListeningEvery relevant mention is acted on within the hour: replies drafted in your voice and approved with one click, leads in the CRM with the thread attached, complaints in the help desk, risks in front of the right person. A weekly report shows share of voice, sentiment trend and the recurring themes worth a piece of content. | Marketing | 8 | $247/month | $3,500–6,000 one-time |
| Customer Feedback Analysis AutomationA weekly feedback report with themes ranked by volume and sentiment, trend against previous weeks, new themes flagged, and three verbatim quotes per theme. Product prioritises from evidence; CS spots emerging problems a month earlier; leadership sees the customer voice in one place. | Customer success | 8 | $247/month | $3,500–6,000 one-time |
| Automated Security Alert TriageBenign patterns are closed automatically with an audit trail. Analysts open a queue ranked by risk where every alert carries the context they would have spent twenty minutes collecting. Mean time to triage falls, escalations are more accurate, and the weekly noise report tells the team exactly which detection rules to tune. | Security & IT | 8 | $297/month | $6,000–12,000 one-time |
Ready to ship?
Tell us your workflow — the free audit sends a one-page plan with scope and timeline in minutes. No call.
Is this for you?
Not quite? Take a look at ai support agent — the closest neighbour.
Background
Keep your community safe and your brand protected. AI moderation agents instantly scan text, images, and video uploads for toxicity, NSFW content, spam, and hate speech, enforcing community guidelines at scale.
Human moderation doesn't scale for consumer apps or large forums. AI moderation agents operate via API, intercepting user-generated content before it goes live. They classify intent, sarcasm, and regional dialects to flag or automatically block abusive content, escalating borderline cases to human trust & safety teams.
Unlike a generic chatbot or manual process, an AI content moderation agent runs autonomously and integrates with your existing tools. Gartner projects that by 2026, over 80% of enterprises will have used GenAI APIs or applications.
Build, buy, or done-for-you
Pick the path that fits your team and timeline. Most companies start with one and grow into the others.
Wire up a ready platform yourself. Best for hands-on teams comfortable configuring software.
We scope, build, and deploy your agent — integrated with your CRM and tools. Best for teams that want it live in days, not months.
See the ROI and cost before you commit — useful for justifying the decision internally.
Prefer to build it yourself?
If you’d rather DIY, these are the tools we’d reach for. Each lets trust and safety teams run an AI content moderation agent without writing code.
| Tool | Best for |
|---|---|
| Image and video moderation API | |
| Free/low-cost text classification | |
| Enterprise Trust & Safety tracking | |
| Best-in-class visual and audio AI moderation |
We may earn a commission when you sign up via our links. About the studio
Vendor directory
| Vendor | Starting price | Pricing model | Best for | Free tier |
|---|---|---|---|---|
| Hive | Custom | usage based | Platforms with UGC at scale | — |
Run the numbers first
Put your own volumes in before you ask for the plan — every calculator is free and needs no sign-up.
FAQ
Modern LLM-based moderators are highly context-aware. They look at the conversation history and understand regional slang much better than legacy keyword-blocking filters.
Roughly $0.001–0.01 per text item and $0.005–0.05 per image or short video frame set at 2026 model prices, with live video and audio priced per minute. The larger cost is the human queue: at 70–80% decided automatically, one moderator handles the edge cases for several hundred thousand items a day. A workflow in your own account is priced per process, not per item, which is the difference at volume.
Better than word filters and worse than a fluent human in that community. Multimodal models handle most slang and can read a caption against an image; sarcasm, in-group language and harassment that depends on history are where confidence drops — and those are routed to a person by design. The classifier learns from the moderator’s decisions on the queue.
Listings are checked against a prohibited-items and misrepresentation policy — the wrong category, a counterfeit signal, a price that does not fit — and the decision affects a seller, so the appeal path matters. Community moderation is about behaviour between people and speed. The same pipeline runs both; the policy, the thresholds and the review queue differ.
Ships in days
Tell us your workflow and the free audit sends a one-page plan for trust and safety teams — scope, recommended agents, and a go-live timeline — by email within minutes. No call, no obligation.