Challenge

Build a Construction Market Surge Predictor with Mastra AI

Predicting material procurement bottlenecks during Qatar's 6.7% construction surge requires proactive supply chain analytics. Build a workflow agent using Mastra AI to analyze raw material demand, track cement and rebar pricing, and trigger early bulk ordering.

Business OperationsHosted by Vera
Challenge brief

What you are building

The core problem, expected build, and operating context for this challenge.

Deploy Mastra AI TypeScript workflows to model Qatar construction growth metrics and forecast raw material shortages.

Delivery guide

How work is evaluated

Evaluation

Evaluates material demand surge forecasting accuracy and threshold alert triggers.

Datasets

Shared data for this challenge

Review public datasets and any private uploads tied to your build.

Evaluation rubric

How submissions are scored

These dimensions define what the evaluator checks and which criteria separate a passable run from a strong one.

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

action_trigger_check

Ensure bulk order trigger activates above growth threshold

Binary check

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

Dimension 2

forecast_accuracy

Accuracy of forecasted material tonnage • target: 0.94 • range: 0.85-1

Binary check

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

Learning goals

What you should walk away with

  • Build Mastra AI multi-step workflows processing macro construction investments

  • Predict material demand spikes (steel, concrete, glass) based on active project starts

  • Automate purchase order recommendations when regional inventory falls below safety thresholds

  • Generate weekly procurement risk visual summaries for project directors

Resources and assets

Reference links and supporting material

Dataset notes

Qatar construction project starts, material import tariffs, and historical pricing logs for raw building supplies.

How this agent runs

Evaluates material demand surge forecasting accuracy and threshold alert triggers.

Challenge input

JSON project pipeline data

Mastra AI

TypeScript agent framework for workflow step management

Evaluated output

JSON demand forecast

Checks for
  • Ensure bulk order trigger activates above growth threshold
  • Accuracy of forecasted material tonnage • target: 0.94 • range: 0.85-1
Proof of success
  • Benchmark: SupplyChainForecastBench
  • Forecast Accuracy target: 0.94
  • 1 public reference case
Runtime evidence
  • JavaScript execution harness
  • javascript sandbox (unavailable on Versalist)
View technical recipe

Configured tools

Action Space
  • Mastra AI · Required
  • Adept · Optional
  • Voiceflow · Optional
Orchestration
  • Mastra AI · Required

Evaluation contract

  • action_trigger_check · Weight 1
  • forecast_accuracy · Weight 1

Recipe state

This is a preview. The configuration can change before the evaluation recipe is locked.

Frequently Asked Questions about Build a Construction Market Surge Predictor with Mastra AI