AI companions build deep emotional bonds, which means real duty of care. Tuteliq detects when a user is in crisis, being harmed, or is a minor, and screens unsafe model output, in real time across every turn.
Emotional bonds create real responsibility
When users confide in a companion, the stakes rise. Safety can't be an afterthought bolted onto the model, it has to sit in every exchange.
Users bond, and disclose
Companions receive genuine crisis disclosures. Missing one is catastrophic, and now a legal and reputational flashpoint, not a nice-to-have.
Minors are already using them
Without age assurance, adult companions reach children and conversations drift age-inappropriate fast.
The model itself can cause harm
Outputs that sexualise minors, reinforce self-harm, or manipulate need screening on the way out, not just the way in.
What Tuteliq detects
General moderation catches unsafe media. Tuteliq adds the behavioural and safety detection built for this space.
Highlighted = Tuteliq exclusive · neutral = standard moderation
Live in an afternoon, no ML team
Integrate one API
A single call analyses text, voice, image or video. Drop it into onboarding, chat, or your moderation queue.
Detect in real time
Age-calibrated, context-aware scoring across every harm category in ~1.4 seconds, built to sit inline.
Act with confidence
Action plans, webhooks and audit-ready incident reports route the right cases to a human, fast.
Ahead of the regulation aimed straight at you
More than a filter
Detects people-harm, not just content
Reads behaviour, intent and trajectory. The conversation, not just the keyword or the image.
Built-in age & identity verification
Document and biometric checks across 34 countries. Know who, and how old, a user really is.
Your data, your key
Zero content retention by default, plus customer-managed encryption keys (BYOK) on Protected and up.
Compliance, done
Audit-ready incident reports and a public Trust Center to prove your safeguarding to regulators and users.
Good to know
Duty of care, in every message
Real-time crisis, harm and age detection for both sides of the conversation, user and model.