Play Browser · 101 plays
Solution plays
Production-grade FAI Protocol plays. Each ships with a manifest, infrastructure code, primitives, and an evaluation suite. All MIT.
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- 05-it-ticket-resolutionsmallOptimize routing rules, confidence thresholds, model selection, KB retrieval quality
Optimize routing rules, confidence thresholds, model selection, KB retrieval quality
- primitives
- 10
- waf
- 3
- industry
- customer-support
- azure
- 13-fine-tuning-workflowsmallOptimize LoRA rank, learning rate, epochs, batch size, compute selection, cost per training run
Optimize LoRA rank, learning rate, epochs, batch size, compute selection, cost per training run
- primitives
- 10
- waf
- 3
- industry
- education
- azure
- 47-synthetic-data-factorymediumOptimize data diversity, statistical accuracy, correlation preservation, generation cost, batch size, temperature for variety
Optimize data diversity, statistical accuracy, correlation preservation, generation cost, batch size, temperature for variety
- primitives
- 10
- waf
- 4
- industry
- manufacturing
- azure
- 54-ai-customer-support-v2largeOptimize intent classification accuracy, reduce unnecessary escalations, improve CSAT scores, tune sentiment thresholds, minimize cost per resolution
Optimize intent classification accuracy, reduce unnecessary escalations, improve CSAT scores, tune sentiment thresholds, minimize cost per resolution
- primitives
- 10
- waf
- 5
- industry
- customer-support
- azure
- 55-supply-chain-aimediumOptimize forecast model parameters, feature selection, reforecast triggers, risk thresholds, safety stock levels, lead time buffers
Optimize forecast model parameters, feature selection, reforecast triggers, risk thresholds, safety stock levels, lead time buffers
- primitives
- 10
- waf
- 4
- industry
- manufacturing
- azure
- 62-federated-learning-pipelinelargeOptimize convergence speed, client selection strategy, DP epsilon/utility trade-off, aggregation weights, round count, learning rate schedule
Optimize convergence speed, client selection strategy, DP epsilon/utility trade-off, aggregation weights, round count, learning rate schedule
- primitives
- 10
- waf
- 5
- industry
- education
- azure
- 91-customer-churn-predictormediumOptimize risk thresholds, feature selection, retention ROI, segment-specific actions
Optimize risk thresholds, feature selection, retention ROI, segment-specific actions
- primitives
- 10
- waf
- 4
- industry
- customer-support
- azure
- 93-continual-learning-agentmediumOptimize memory retention TTL, distillation thresholds, reflection frequency, retrieval relevance
Optimize memory retention TTL, distillation thresholds, reflection frequency, retrieval relevance
- primitives
- 10
- waf
- 4
- industry
- education
- azure