Gig Worker Grievance Redressal Workflow using Mastra AI
Service platforms require automated, audit-trailed resolution workflows for service provider disputes and ratings appeals. Build a stateful grievance handler using Mastra AI with integrated memory vectors and rule tools to resolve standard worker dispute tickets with 90%+ resolution agreement against human judge benchmarks.
What you are building
The core problem, expected build, and operating context for this challenge.
Build an automated gig economy grievance triage and resolution agent workflow using Mastra AI stateful workflows and vector memory.
How work is evaluated
Evaluates grievance resolution accuracy and payout calculation logic.
Shared data for this challenge
Review public datasets and any private uploads tied to your build.
How submissions are scored
These dimensions define what the evaluator checks and which criteria separate a passable run from a strong one.
policy_clause_reference_check
Verifies that all rulings cite a valid policy clause string.
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
resolution_agreement
Agreement rate with human benchmark rulings. • target: 0.9 • range: 0-1
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
What you should walk away with
Build complex workflows using Mastra AI in TypeScript
Utilize Mastra vector memory to recall historical dispute precedents
Implement multi-step escalation logic for complex customer-partner disputes
Validate worker compensation adjustments against platform terms of service
Reference links and supporting material
150 gig worker dispute appeal transcripts and gold benchmark resolutions.
How this agent runs
Evaluates grievance resolution accuracy and payout calculation logic.
Challenge input
JSON containing ticket_id, partner_id, dispute_type, worker_statement, and customer_rating.
Mastra AI
Offers stateful TS workflows and built-in memory management.
Evaluated output
JSON containing resolution ('FAVOR_WORKER', 'FAVOR_CUSTOMER', 'NO_ACTION'), payout_compensation, and policy_clause.
- Verifies that all rulings cite a valid policy clause string.
- Agreement rate with human benchmark rulings. • target: 0.9 • range: 0-1
- Benchmark: Grievance Arbitrator Evaluation Benchmark
- Resolution Agreement target: 0.9
- 1 public reference case
- JavaScript execution harness
- javascript sandbox (unavailable on Versalist)
View technical recipe
Configured tools
- Mastra AI · Required
- RAI · Optional
- Ellipsis · Optional
- Mastra AI · Required
Evaluation contract
- policy_clause_reference_check · Weight 1
- resolution_agreement · Weight 1
Recipe state
This is a preview. The configuration can change before the evaluation recipe is locked.