How it works
StayClear predicts high-risk gambling moments before they happen. User profile signals, calendar patterns, global event context, delivery data and integration feeds are turned into timely interventions before the next deposit, bet or chase becomes automatic.
StayClear compares personal context, timing patterns, transaction signals, event data and delivery history to decide when a reminder should be sent.
Risk attributes can be derived from a completed profile, schedule, reminder history and consented context.
Potential timing combinations across payday, late night, sport, debt, work, isolation and loss-chasing windows.
Transaction, operator or banking signals can be added where an institution chooses to integrate them.
StayClear captures what generic safer-gambling tools miss: the moments, wording, pressures and personal commitments that actually matter to the user. Payday is not the same risk for everyone. A fixture is not the same risk for everyone. A late-night reminder only works if it understands why that hour is dangerous.
The profile is normalised into structured signals: recurring times, monthly dates, sport categories, urgency, trigger language, message tone, delivery channel, failed sends, completed setup, plan tier and account state. Every signal helps the platform decide when an intervention is useful rather than noisy.
For banks, operators and employers, StayClear can be extended with consented feeds such as gambling-block events, safer-gambling triggers, support referrals, payment-risk categories, transaction alerts, payroll cycles or benefit access rules. The core product works without those feeds; the institutional version becomes stronger with them.
StayClear turns raw context into an intervention sequence that is specific, timed and measurable.
User profile, schedule, sports interests, reminder wording, account state, delivery history and institution-specific signals where available.
Free-text context is mapped into a controlled taxonomy of risk windows, urgency levels, channel rules and message constraints.
The system ranks upcoming windows by timing, recurrence, urgency, recent activity, known triggers and the cost of missing the intervention.
AI can draft reminder language inside strict safety boundaries: no gambling prompts, no bonus language, no clinical claims, and SMS kept within one segment.
Email and SMS delivery are queued, logged and monitored with operational visibility into sent, failed and pending interventions.
Activation, profile completion, edits, delivery reliability, failed sends, cancellation and institutional outcomes create the feedback loop for better timing and stronger prompts.
StayClear is built as prevention infrastructure, not a lightweight reminder tool. The platform brings together profile setup, risk-window scoring, message rules, email and SMS delivery, subscription state, consent controls, admin monitoring and reporting in one system.
That matters for organisations that need more than a scheduled text. They need a product that can be funded, governed, measured and integrated without turning personal reminders into marketing data or exposing private user notes to operational teams.
Individuals can use StayClear today with no institutional integration. Public health teams, operators, banks and employers can add data sources, governance rules and reporting needs around the same core intervention infrastructure.
