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Casino & Mixed-Use Non-Gaming Revenue Optimizer with Mastra AI

Shift in customer demographics toward digital betting forces physical regional casinos to optimize non-gaming spatial revenue (dining, entertainment, retail). Build an agentic pipeline using Mastra AI in TypeScript to reallocate square footage dynamically based on foot-traffic telemetry. Increase projected non-gaming yield by 15%+.

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What you are building

Develop a spatial yield optimizer using Mastra AI agent steps to maximize non-gaming revenue for hospitality real estate.

How work is evaluated

Evaluation

Evaluates floorplan space reallocation recommendations and projected RevPASF improvements.

Datasets

Public datasets, plus the private datasets you have access to.

How submissions are scored

Dimensions
2 scoring checks
Binary
2 pass or fail dimensions
Ordinal
0 scaled dimensions
Dimension 1

Total Area Preservation

Reallocated space must equal total available area

Binary check

This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.

Dimension 2

Yield Optimization Factor

Projected revenue gain percentage achieved by recommendation • target: 15 • range: 5-30

Binary check

This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.

Learning goals

  • Implement Mastra AI workflows for spatial revenue optimization

  • Process sensor foot-traffic densities across physical floor plan zones

  • Dynamically reallocate underperforming gaming floor space to high-margin amenities

  • Output optimal floorplan square footage allocations with expected ROI

Resources

Dataset notes

Foot-traffic sensor telemetry and hourly revenue per square foot records from regional casino complexes.

Challenge setup

Evaluates floorplan space reallocation recommendations and projected RevPASF improvements.

Challenge input

JSON with total_sqft, current_slot_sqft, dining_foot_traffic_index, slot_rev_per_sqft, dining_rev_per_sqft

Mastra AI

Provides modular TypeScript workflows and step engine

Evaluated output

JSON with recommended_slot_sqft, recommended_dining_sqft, projected_rev_increase_pct

Evaluation checks
  • Reallocated space must equal total available area
  • Projected revenue gain percentage achieved by recommendation • target: 15 • range: 5-30
Configured evaluation evidence
  • Benchmark: SpatialYieldBench
  • Yield Optimization Factor target: 15
  • 1 public reference case
Configured runtime
  • JavaScript execution harness
  • javascript sandbox (unavailable on Versalist)

Shows the first task, up to three tools, and up to three evidence items.

View technical recipe

Configured tools

Action Space
  • Mastra AI · Required
  • Bland AI · Optional
Policy Serving
  • Vercel AI Gateway · Optional
Orchestration
  • Mastra AI · Required
  • Vercel AI Gateway · Optional

Evaluation contract

  • Total Area Preservation · Weight 1
  • Yield Optimization Factor · Weight 1

Metrics

  • Yield Optimization Factor · Target 15

Benchmarks

  • SpatialYieldBench
  • general

Reference cases

  • 1 public reference case

Workflow tasks

  1. Task 1

    Input: JSON with total_sqft, current_slot_sqft, dining_foot_traffic_index, slot_rev_per_sqft, dining_rev_per_sqft

    Output: JSON with recommended_slot_sqft, recommended_dining_sqft, projected_rev_increase_pct

    Execution harness: JavaScript

Evaluation tools

  • Mastra AI · Agent System Framework

Recipe freeze marker

No recipe freeze time is recorded.

Frequently Asked Questions about Casino & Mixed-Use Non-Gaming Revenue Optimizer with Mastra AI