- A score appears and no one can explain why
- AI output reaches the student with no staff gate
- Trust documents list features the tool cannot perform
SUPERVISED BY DESIGN
Supervised, advisory, transparent, auditable — and human-owned.
A child's data, a child's work, and a child's next step deserve a system you can inspect. Outleap keeps AI assistance supervised and bounded, puts your school in control of the feedback students receive, scopes access to role, and never trains on pupil data. The Opportunity Radar described here is in development; its guardrails are designed in, not bolted on.
THE PROCUREMENT READ
From a black box you have to trust to a system you can inspect.
Most AI tools ask a school to take the model's word for it. Outleap is built the other way round. Every AI step is supervised, bounded and under your school's control, and the trust pack describes only what is processed today.
- Your school controls the feedback students receive
- Access is scoped to role; no training on pupil data
- Trust pack scoped to what we actually process today
THE GUARDRAILS
Live today, and built to extend.
Some guardrails govern the product as it runs now. Others are designed into the Opportunity Radar that is still in development. We keep the two clearly separated, so a trust review never confuses a live control with a roadmap intention.
School-controlled feedback (live)
AI feedback is supervised and bounded, and your school stays in control: it sets the controls, can require staff review before release, and anything flagged as a concern is always held for a member of staff. This is the same human oversight the Opportunity Radar is being built to follow.
Role-scoped access, no training on pupil data (live)
Access is scoped by role and by school, and tenancy is strictly separated. We do not train models on pupil data; statements, evidence and feedback are processed to run the service for your school, not to improve a model used elsewhere.
Supervised radar guardrails (in development)
The Opportunity Radar is being built so every suggestion carries a source, a reason it is shown and a verified date, with no auto-submit and no hidden sensitive-data profiling. These ship with the radar, not before.
ICO CHILDREN'S CODE
Designed for an under-18 cohort.
This is a service for children, and the Children's Code is the standard a cautious Data Protection Lead looks for first. We name our alignment in plain school-facing language, not only in the legal documents.
High privacy by default
Settings start private. A student controls their own progression profile, and nothing about a child is exposed more widely than the school's process requires.
Best interests of the child
Design choices are made for the student's benefit. There are no nudges that weaken a child's privacy, and no dark patterns pushing a young person to share more.
Data minimisation
We collect what the progression process needs and no more. Metrics measure quality movement such as a route recorded or timely support before a deadline, never vanity counts of clicks.
DFE GENERATIVE-AI GUIDANCE
Aligned to how the DfE expects AI to be used in schools.
The DfE's guidance on generative AI in education sets clear expectations. We map to them on the page, so your IT lead and DPO can check the posture before they read a single policy document.
Transparency
AI involvement is visible, not hidden. Feedback is clearly labelled as supervised AI assistance under your school's control, and the radar is being built so every suggestion shows its source and a human-readable reason.
No training on pupil data, with fact-checking
Pupil data is not used to train models, and AI output is treated as advisory — never a verdict on a child. Your school sets the controls, can require staff review, and anything flagged as a concern is held for a person to check.
DPO and IT involvement
The trust pack is written for your DPO and IT lead to interrogate. We expect involvement from data protection and IT, and we scope our documents to what we actually process so that involvement is straightforward.
WHAT YOUR DPO READS FIRST
Scoped to what we actually process.
The trust pack describes today's processing: the Evidence Bank, the UCAS three-question statement workflow, school-supervised managed feedback, and references where enabled. CV, cover-letter and competency processing are not listed as current use, because they are on the roadmap and not yet built. Lawful basis sits with you as controller, documented in your own DPIA. We give you accurate inputs, not a binding misstatement to inherit.
Procurement path
Trust documents that can support school review.
School leaders, safeguarding teams, and procurement reviewers should be able to see the core documents before a rollout conversation gets stuck in document chasing.
Data Processing Agreement
Controller-processor terms for school procurement and legal review.
DPIA starterA practical starting point for school Data Protection Impact Assessment review.
Retention policyRetention categories, review cadence, and deletion posture for school data.
AI safety policyBounded, supervised AI usage, review controls, transparency, and school-facing safeguards.
FOR DATA, IT AND DPOS
Read it through the lens of a 17-year-old's data.
Bring your DPO, IT lead and DSL. We will walk the school's feedback controls and safety holds, role-scoped access and the no-training position, then hand over the trust pack so your DPIA describes only what we actually process.
Book a trust review