Ship child-safe apps without building content moderation from scratch
Tuteliq is a content moderation API aligned with KOSA. Detect grooming, bullying, self-harm, and more — with age-calibrated risk scoring in under 400ms. One API call replaces months of in-house ML work.Get API Key — Free
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Read the Docs
Follow the quickstart guide to make your first API call.
Built for platforms where minors interact online — from gaming chat to classroom apps.
The problem
Child safety compliance shouldn’t require a machine learning team. KOSA requires platforms to protect minors from nine categories of harm — bullying, grooming, eating disorders, substance use, self-harm, depression, compulsive usage, sexual exploitation, and unsafe visual content. Building detection for even one of these categories takes months of ML engineering, training data, and ongoing maintenance. Building for all nine, across text, voice, and images, with age-appropriate calibration? That’s a team-year of work. Tuteliq does it in a single API call.Safety Detection
Per-message risk scoring for bullying, grooming, self-harm, substance use, and more — calibrated by age group and aligned to all nine KOSA harm categories.
Emotional Analysis
Track emotional trends over time to catch depression, anxiety, and declining mental health before they escalate — not just per-message, but across entire conversation histories.
Voice & Image
Process audio recordings and images for safety analysis, including transcription, OCR, and content classification.
Batch & Webhooks
Submit bulk analysis jobs and receive results asynchronously via webhook callbacks.
KOSA Compliance
Built-in coverage for all nine Kids Online Safety Act harm categories with audit-ready reporting.
GDPR Ready
Data minimization, retention controls, and consent management designed for processing children’s data.
Why Tuteliq
Age-Calibrated Severity
A joke between 16-year-olds isn’t the same as a message to an 8-year-old. Risk scores automatically adjust across four age brackets so your moderation matches developmental context.
Context, Not Keywords
A teen texting “I’m literally going to die if I don’t get those shoes” shouldn’t trigger the same response as genuine crisis language. Tuteliq’s context engine understands the difference — dramatically reducing false positives.
Beyond Detection
Most safety APIs stop at a risk score. Tuteliq generates age-appropriate action plans for children, parents, and moderators, plus professional incident reports ready for school counselors and compliance audits.
Full KOSA Coverage
Nine out of nine harm categories covered out of the box. No mix-and-match from multiple vendors. One integration, full compliance.
Multimodal
Text, voice, and images analyzed through a single API. Audio is transcribed and safety-analyzed with timestamped segments. Images are classified visually and OCR-scanned for embedded text.
Built for Production
Sub-400ms latency. 99.9% uptime SLA. Batch processing for up to 50 items per request. HMAC-signed webhooks with automatic retry. GDPR-compliant data management on every tier.
Who uses Tuteliq
Built for platforms where minors interact:- Gaming platforms — Moderate in-game chat, voice comms, and user-generated content in real time.
- Social apps — Detect grooming, bullying, and self-harm signals in DMs and feeds before they escalate.
- Ed-tech — Ensure safe learning environments with content filtering that understands classroom context.
- Messaging apps — Analyze conversations for emotional distress and predatory behavior across text and voice.
Performance
| Metric | Value |
|---|---|
| Average response time | < 400ms |
| Uptime SLA | 99.9% |
| KOSA categories covered | 9/9 |
| Supported input types | Text, voice, image |
| Rate limits | 60–5,000 req/min depending on tier |
| Credit costs | 1–5 credits per call — see Pricing & Credits |
Get started
Quickstart
Get up and running with Tuteliq in under 5 minutes.