Real-money operations breakwhen they rely on manual loops.
Trustplay builds the infrastructure layer for operators who need live event monitoring, scoped automation, human approvals, and auditability across casino operations and Base-native prediction markets.
Login anomaly matched against shared fraud memory.
Player withdrawal context attached to open support thread.
High-value action denied. Human approval required.
Offer recommendation adjusted after risk signal.
Event-market resolution waiting on verified source.
Decision trace sealed to operator control room.
Headcount does not scale. Agents do.
The old model
Trustplay aOS
One operating system. Every agent speaks the same language.
Shared Memory
The moment the risk engine spots a new fraud pattern, support and VIP agents already know about it. Nothing sits in a silo waiting to be rediscovered.
Deterministic Compliance
Agents operate inside cryptographically defined scopes. An action outside its scope does not get discouraged - it cannot execute. High-value actions route to a human automatically.
Event-Driven, Not Prompted
aOS is wired into your platform's live activity stream. A withdrawal, a login anomaly, a bonus pattern - it responds the instant it happens.
Human-Approved Learning
Agents cannot rewrite your rulebook. When they hit a gap or an outdated procedure, they propose a fix. Approve it once and every agent has it moments later.
The Control Room
One dashboard, every decision. Audit the exact reasoning behind any agent action, step into a live session, and correct course on the fly.
From event to outcome, in one continuous loop
Event fires
A login anomaly, withdrawal, player complaint, bonus pattern, or market event hits the live activity stream.
Agent assesses
The right agent checks shared memory, current rules, player or market context, jurisdiction, and risk boundaries.
Act or stage
Low-risk actions execute inside scope. Sensitive actions are prepared with evidence and staged for an operator.
Human decides
A human approves, rejects, takes over, or converts the lesson into a rule that every agent can use.
From signal to action, without losing control.
Event
Login anomaly, withdrawal, or market trigger enters the live stream.
Agent
The right agent evaluates context using shared memory and current rules.
Policy
Scope and jurisdiction checks decide whether the action can execute.
Human
Sensitive actions route to a human approval layer instead of running blind.
Audit
Every action and decision is written back into the control room trace.
aOS did not start as a demo. It started as infrastructure.
Player Account Management
Accounts, wallets, KYC touchpoints, balances, sessions, limits, and operational controls.
Remote Gaming Server
Game delivery infrastructure built for certified real-money environments.
Live Streaming
Live content, studio operations, and operator-facing production workflows.
Trustplay Verity for Base-native prediction markets
CLOB Trading
Central limit order book markets - not bonding curves - the market structure operators and traders already understand.
USDC on Base
Settlement in USDC on Base: low-cost, fast finality, fully on-chain.
Market Lifecycle
Creation, claim, and operator workflows, from first trade through final resolution.
Operator Controls
Production-grade admin controls for market visibility, jurisdiction handling, and restricted-topic enforcement.
Oracle Resolution
Oracle-based resolution where applicable, so outcomes stay verifiable and outside any single party's control.
Live Dashboards
Markets, volume, fees, owners, and activity - visible in real time, with the same discipline as the Control Room.
Blizz Markets is not the pitch. It is the forge.
Verity is informed by a live operator environment where market lifecycle, admin controls, and resolution flows have to survive actual use instead of looking pretty in a mockup.
Autonomy, without giving up control
The biggest objection to agentic AI in a regulated business is not capability - it is trust. aOS is built around one rule: agents can act fast, but never outside what you have explicitly allowed.
agent: withdrawal.agent
requested_scope: payout:release
allowed_scope: payout:evaluate
decision: denied
route: human_approval_queue
For operators who need control, not AI theater
Book a working session and we will map your current stack, show where scoped automation actually saves operator time, and show where human approvals stay in the loop.
Book a demo