Social media content moderation API and child safety software for social platforms. Real-time grooming, sextortion and CSAM detection. KOSA, DSA, UK OSA.

A social media content moderation API built for the harms that now start with a generated image. Detect AI-generated nudes, synthetic media and the coercive DM patterns behind sextortion, alongside grooming, bullying and CSAM, in real time.

Why social platforms need dedicated child safety software

Generic content moderation tools miss the behavioural patterns that put minors at risk. Social platforms face the most complex child safety challenges, at scale, across modalities, and under increasing regulatory scrutiny.

Scale of content

Millions of messages, posts, and interactions daily, manual moderation can't keep up

Grooming in DMs

Private messaging is the primary vector for child exploitation on social platforms

Multi-modal content

Text, images, video, and voice all need analysis, not just text

Regulatory pressure

KOSA, DSA, UK OSA, and COPPA all impose specific obligations on social platforms

Multi-modal content analysis

Every content type. Every risk category. One API.

Real-time Chat Analysis

Detect grooming, bullying, and coercive control in DMs and group chats

Image Safety

Analyse images for CSAM indicators, age-inappropriate content, and synthetic media

Video Analysis

Detect harmful content in video uploads and live streams

Sextortion Detection

Identify coercive patterns targeting minors for sexual exploitation

Romance Scam Detection

Detect social engineering and financial exploitation targeting young users

Synthetic Content Detection

Identify AI-generated deepfakes and manipulated media

Deepfake detection and sextortion prevention

Sextortion no longer needs a real image. An offender can take photographs from a public profile, run them through a nudification tool, and open with the threat. Detecting that means scoring the media and the conversation together, because the coercion usually arrives before the file does.

Full capability detail, latency and pricing on the deepfake detection API page.

Synthetic media detection

Score uploaded images and video frames for signs of AI generation or manipulation before they reach a feed, a DM or a live stream.

Coercive pattern detection

Read the conversation, not just the file. Sextortion follows a recognisable arc: rapid intimacy, a request for an image, then a threat and a payment demand.

Minor-context escalation

When a synthetic sexual image is tied to a minor account, Tuteliq raises severity to the maximum and returns an escalate action rather than a queue-for-review action.

Auditable decision trail

Every detection returns a risk score, harm categories and a recommended action, logged for regulator reporting without retaining the underlying media.

What detection can and cannot tell you

Synthetic media detection is probabilistic. Tuteliq returns a confidence score, not a verdict, because generation tools change faster than any detector can claim certainty. Most platforms set a high threshold for automatic removal and a lower one for human review, so a borderline image reaches a moderator rather than a false takedown. The conversational signal is often the stronger one: a threat and a payment demand are unambiguous even when the attached image is not.

Social media moderation use cases

Where social platforms apply Tuteliq across the product surface, from first message to public feed.

Direct message screening

Score every DM between an adult account and a minor account before delivery, without storing message content.

Signal: grooming, sextortion, coercive control

Public feed and comments

Screen posts, replies and comment threads for bullying, self-harm promotion and age-inappropriate material.

Signal: bullying, self-harm, adult content

Media uploads

Analyse images and video frames at upload time for CSAM indicators and manipulated media before they reach a feed.

Signal: CSAM indicators, synthetic media

Live streams and voice rooms

Sample audio and frames during live sessions so moderators are alerted while a stream is still running.

Signal: voice grooming, harmful live content

New account and follow requests

Flag adult accounts systematically contacting minor accounts, a behavioural pattern single messages never reveal.

Signal: contact patterns, age mismatch

Moderator queue triage

Rank reports by risk score so the highest-harm cases reach human moderators first, with an auditable decision trail.

Signal: risk score, recommended action

How to integrate the moderation API

Call Tuteliq inline before a message or upload is delivered, or asynchronously from your event stream. Responses return a risk score, categories and a recommended action your moderation queue can enforce.

Authenticate

Create an API key in the dashboard and send it as a bearer token from your backend, never from the client.

Send content with context

Include surface type, platform and user age band so the model calibrates to the conversation, not just the words.

Act on the response

Use risk_score and recommended_action to block, hold for review or escalate, and log the decision for regulator reporting.

Full request and response schemas live in the API reference, with SDKs for Node.js, Python, Kotlin, Swift and Unity.

Multi-jurisdictional compliance

Social platforms operate globally. Tuteliq helps you comply everywhere.

KOSA

All 13 harm categories covered

COPPA

Zero content retention, no PII storage

EU DSA

Transparency reporting and content actioning

UK OSA

Risk assessment and proactive scanning

Zero content retention

1.1-1.5s typical latency

32 languages

Multi-modal analysis

Common questions

What is deepfake detection?

How does deepfake sextortion work?

Can you detect AI-generated nudes and nudification apps?

What is a sextortion prevention API?

What is a social media content moderation API?

Can Tuteliq handle the scale of social media content?

Which regulations does Tuteliq help social platforms comply with?

How do you integrate content moderation into DMs and feeds?

Related: Gaming platforms, KOSA compliance, UK Online Safety Act guides, API reference.

How to add child safety detection to a social platform

Add real-time grooming, bullying, and exploitation detection to feeds, comments, and direct messages in five steps.

  • 1 Create an account and API key Sign up, verify your email, and generate an API key from the dashboard. Test and live keys are separate, so you can integrate without touching production traffic.

Create an account and API key

Sign up, verify your email, and generate an API key from the dashboard. Test and live keys are separate, so you can integrate without touching production traffic.

  • 2 Send your first request Post posts, comments, or direct messages to the relevant detection endpoint over HTTPS, either directly or with one of the SDKs. The response returns a risk category, a risk score, and a recommended action. No content is stored.

Send your first request

Post posts, comments, or direct messages to the relevant detection endpoint over HTTPS, either directly or with one of the SDKs. The response returns a risk category, a risk score, and a recommended action. No content is stored.

  • 3 Map risk levels to your actions Decide what each risk level triggers on your platform: log only, queue for human review, restrict the interaction, or escalate. Thresholds are configurable per risk category.

Map risk levels to your actions

Decide what each risk level triggers on your platform: log only, queue for human review, restrict the interaction, or escalate. Thresholds are configurable per risk category.

  • 4 Connect webhooks and your review queue Register a webhook endpoint so high-risk events reach your trust and safety team in real time, and review them in the Tuteliq console or in your own tooling.

Connect webhooks and your review queue

Register a webhook endpoint so high-risk events reach your trust and safety team in real time, and review them in the Tuteliq console or in your own tooling.

  • 5 Review evidence and reporting Use the incident log, audit trail, and transparency reporting to evidence your safety measures for regulators, auditors, and internal governance.

Review evidence and reporting

Use the incident log, audit trail, and transparency reporting to evidence your safety measures for regulators, auditors, and internal governance.

Protect your community

See how Tuteliq scales child safety across your platform, from DMs to public feeds.

FOR DEVELOPERS

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