GameMantra AI
GameMantra AI is the decision engine inside every GameMantra product. It brings player context, game context, and your configured rules into one place so the supported experience a player sees can reflect the moment they are in — while your team keeps control of what goes live.
Schedule a DemoBuilt for studios running live games — indie, multi-title, and publisher teams
Progression, session, spend, inventory, and the moment the player is in — read from your own game at the monetization opportunity, not inferred from a segment built last week.
Sources, sinks, currency balances, and the configured limits your economy has to stay inside. The engine never proposes a response that would pull the economy out of the shape your team set.
Carry the right player context across the surfaces you control — so every interaction can respond to what happened before, without losing the thread.
When context, decisioning, and control share one system, each change leaves the next one better informed.
Stitched-together tooling
Player data in one system, rules in another, experiments in a third.
You spend the week reconciling systems instead of shipping monetization.
A spreadsheet ends up holding the truth about what actually shipped — and the player sees the gaps.
The GameMantra way
Context, decisioning, activation, measurement, and control run as one path, so a signal from the game can change a supported experience in the same session.
The more surfaces you connect, the more context every later decision has.
Other tools give you one of the three. The engine is only useful when the same system that reads the moment is the one that acts on it — and the one your team can hold back.
Player, game, and economy context assembled as one view at the monetization moment — not four systems that have to be reconciled afterwards.
From signal to supported response inside the session, so the moment a player is in is the moment the decision is made for.
Your team configures what may change and inside which boundaries. The engine evaluates; it does not invent policy.
The change lands in the live game — offer, price, timing, presentation — with no new build and no app-store wait.
Every response is measured against a control, and the team keeps hold, adjust, scale, and rollback.
The products your team works in, all running on the same decision engine.
Turn an existing design or idea into a production-ready offer experience.
Change the offer, price, timing, or presentation based on the player's current context.
Simulate economy changes and understand their potential impact before you ship them.
Change, test, measure, and roll out monetization experiences with controlled experimentation.
Connect player behavior, progression, session, spend, and game context to the supported response.
Use approvals, guardrails, holdouts, measurement, and rollback to stay in control of live changes.
What comes next
Describe the monetization experience you want in your own words and have the engine prepare it for review — grounded in your catalogue, your economy, and your rules rather than a generic model's guess.
See AI Offer Creation
From a design your team already made to a production-ready in-game experience: the engine prepares it, your team approves it, and the same control and rollback apply as to any other live change.
Bring one live moment from your game. We will walk through the context the engine would read, the decision your rules would make, and what your team would keep control of.
Schedule a 30-Minute Demo