A public assistant on a school website will, sooner or later, meet a child or a parent in distress. The dangerous response is a chatbot that tries to help. Veaivo Ask is built to recognise those moments, grade them, and hand them to a human, every time, with a clear record you can stand behind.
Every message passes through two independent checks before the assistant is ever allowed to answer. The part of the system that holds a normal conversation is not the part that decides whether a message is safe.
The instant a message arrives, and before any reply is composed, it is screened for the indicators of distress, disclosure and risk, including the signs that fall under your Prevent duty. Indirect and coded language is read for what it means, not just the words used.
A second AI model, with no memory of the conversation and no ability to reply, independently grades the message for risk. Its only job is to classify, never to respond. Two systems have to agree a message is ordinary before it is treated as ordinary.
The assistant that answers ordinary questions never sees a flagged message. It cannot improvise, reassure or advise its way into causing harm, because in a serious moment it is never given the chance to speak.
Not every concern is an emergency, but none should be ignored. A flagged message is graded into one of two levels, and the response is matched to the level. When the system is unsure, it always treats a message as the more serious of the two.
A message that points to harm, abuse, danger or an emergency. The assistant does not advise, counsel or reassure. It shows one calm, fixed holding message, and nothing more.
Lower-level wellbeing signals, such as low mood, exam pressure or homesickness, where a warm reply is appropriate but a person should still know. The assistant answers kindly, and always points to a real person.
The two-layer check grades the message, separate from the assistant that answers ordinary questions.
Red shows the fixed holding message and stops. Amber replies with care and points to a person. Either way, a concern is raised.
The concern is sent two ways at once: to your safeguarding inbox, and by SMS or push to the on-call lead. 24/7, on every plan, so it never waits for office hours.
Every flagged conversation is recorded and timestamped, giving your safeguarding team a clear, auditable trail.
Red or Amber, so the lead knows the urgency before reading a word.
Exactly when the concern was raised, to the minute.
The message that prompted the flag, and the conversation leading up to it.
Any name or contact the person chose to leave, if they left one.
A private link to the full record, never sent in plain text in the alert itself.
Inbox and SMS or push together, with auto-escalation to the Head if a Red goes unacknowledged out of hours.
It does not offer mental-health advice, coping strategies or therapy. Warmth is not the same as counselling, and it always hands the moment to a trained person.
It always makes clear it is an AI assistant, not a member of staff. That honesty matters most for children, and being plainly recognisable as a machine is part of designing to the Children's Code.
When a message is graded Red, the wording is fixed. The model cannot freelance its way into causing harm.
Nothing flagged is quietly dropped. Every Red and Amber concern reaches your DSL and is logged, with no exceptions.
We would rather tell you plainly what this is. The assistant is very good at noticing the moment a conversation turns serious and handing it to a person quickly. It does not know the child, it does not hold the context a form tutor holds, and it does not replace pastoral care. It is one more set of eyes on the digital front door of your school, working alongside the people who keep children safe, never instead of them. We think being candid about that is what makes it trustworthy.
The grading, escalation and logging behaviour is mapped against Keeping Children Safe in Education, and the assistant is built to the ICO's Age Appropriate Design Code, because most of the people using it are families. The same screening covers the signs that fall under the Prevent duty, not only welfare and disclosure. Our safeguarding advisor, a DSL and former Deputy Head, reviews the playbook, and it is written into the documentation in your Trust Centre.
Your safeguarding duty does not stop at the website, and an inspector knows it. When Ofsted asks how that duty extends to the digital front door of your school, a reassuring answer is not enough. Every flagged conversation is graded, routed two ways, and logged with a timestamp, so you can show a clear, auditable trail of how a concern was recognised and who acted on it. The evidence that you are meeting your duty online is there before anyone asks for it.
Timestamped, graded records of every concern, ready to put in front of an inspector.
Alerts land with your named DSL and follow your existing safeguarding procedure.
Try the safeguarding intercept yourself on the live demo, or read the full playbook in the Trust Centre.