Validate your slot math. Improve the player experience.
Meeting your RTP target is just the beginning. Kairos, our proprietary player model trained in-house at reSlot, predicts how long different players will play, how likely they are to return the next day, and how much they will wager. Loop keeps testing and refining configurations, helping you balance retention, costs and returns.
One plan, three metrics evaluated together
Understand each player type’s outcomes before deciding what to optimize.
The animation illustrates possible trade-offs using the starting values and outcomes of synthetic experiments. Intermediate rounds are generated for the demo.
28 days · 10 seeds per setting
Synthetic players, Bonus off. Shows research results, not live data or Kairos predictions.
Total payouts ÷ total wagered. This is the actual result from simulated behavior, not the theoretical RTP on the paytable.
The expected share of players who return on the second day under a given player cohort and game configuration. This shows estimates from a synthetic experiment, not measured live retention.
Net compensation minus suppression recovery, as a share of total wagered. Negative values mean control recovery exceeded compensation spend.
More likely to follow stop-loss and take-profit limits. The same game configuration produced different return behavior and cost structures.
The original control configuration used as the study control, kept unchanged.
An illustrative trajectory based on published synthetic experiments. Intermediate rounds are generated for the animation, not measured results or live AI predictions. They do not guarantee performance.
Kairos / Player outcomes
| Game | RTP | Hit frequency | Volatility | Predicted session length | Expected D2 retention | Turnover per player |
|---|---|---|---|---|---|---|
| Demo A | 96.2% | 27.9% | 7.1 | 142 spins | 31% | 218× |
| Demo B | 94.7% | 24.7% | 8.6 | 118 spins | 27% | 186× |
| Demo C | 92.1% | 20.1% | 10.3 | 96 spins | 22% | 151× |
Illustrative figures showing how metrics are compared; these are not predictions for your game.
Built on Loop Engineering for Self-Improving Slot Agents ↗Find your starting point
Preparing a game for certification, managing live operations or building with AI? Start with the decision in front of you.
Certified studios
Compare player outcomes alongside the numbers in your PAR sheet.
Dynamic control
Evaluate compensation cost alongside retention to find configurations worth adjusting.
LLM studios
Generate, simulate, validate and refine in one loop.
From one sheet to the full portfolio
Import a PAR sheet, weight table, or control configuration to check RTP, hit frequency, and cost. Run a browser simulator first, then decide what needs deeper optimization.
Kairos learns player behavior from your spin stream and predicts session length, next-day retention, and turnover. Compare different outcomes by segment under the same math configuration.
Loop simulates candidate designs, compares metrics, and checks budget and risk constraints. Feed the results into the next cycle to continuously manage games and player portfolios.
Pricing
Choose the level of support that fits your goals.
Bring your existing PAR sheet, weight table, or AI draft. We run the validation and tuning loop, then deliver a recalibrated design, change notes, and an evaluation report so you can decide the next step with evidence.
We train Kairos on your player data and handle deployment, ongoing updates and day-to-day operations. Connect to our API to let Kairos and Loop keep evaluating configurations and improving your player and game portfolio, without building or maintaining the model yourself.
See the evidence before you decide
Run a sample PAR sheet to view exact RTP, simulation results, and target tuning.
ViewCompare cost and player outcomes under control configurations and view the simulation results.
ViewLearn how Kairos studies player behavior, simulates response, and evaluates predictions.
ViewReview Loop methods and experimental results to understand which changes work and under what conditions.
ViewStart with your next decision
Want to reduce pre-submission iteration, evaluate a compensation budget, or validate an AI-generated design? Tell us which metric you want to optimize, and bring a PAR sheet, weight table, or draft. Together we’ll define the evaluation scope, deliverables, and next step.