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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- 53-legal-document-aimediumOptimize clause detection accuracy, risk score calibration, redline quality, processing throughput for large contracts, clause library coverage
Optimize clause detection accuracy, risk score calibration, redline quality, processing throughput for large contracts, clause library coverage
- primitives
- 10
- waf
- 4
- industry
- general
- 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
- 56-semantic-code-searchmediumOptimize embedding model selection, boost weights (docstring vs code vs comments), query rewriting, top-k, score threshold, indexing cost
Optimize embedding model selection, boost weights (docstring vs code vs comments), query rewriting, top-k, score threshold, indexing cost
- primitives
- 10
- waf
- 4
- industry
- developer-tools
- azure
- 59-ai-recruiter-agentmediumOptimize matching accuracy, reduce disparate impact, calibrate scoring weights, tune PII detection recall, minimize cost per screening
Optimize matching accuracy, reduce disparate impact, calibrate scoring weights, tune PII detection recall, minimize cost per screening
- primitives
- 10
- waf
- 4
- industry
- general
- azure
- 60-responsible-ai-dashboardmediumOptimize monitoring cadence, alert thresholds, executive summary quality, report scheduling, intersectional group coverage
Optimize monitoring cadence, alert thresholds, executive summary quality, report scheduling, intersectional group coverage
- primitives
- 10
- waf
- 4
- industry
- general
- azure
- 61-content-moderation-v2mediumOptimize per-category severity thresholds, reduce false positives, tune custom blocklists, improve review queue throughput, minimize latency
Optimize per-category severity thresholds, reduce false positives, tune custom blocklists, improve review queue throughput, minimize latency
- primitives
- 10
- waf
- 4
- industry
- media
- 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
- 63-fraud-detection-agentlargeOptimize detection thresholds per transaction type, reduce false positives, tune velocity windows, calibrate ML model, improve graph analysis depth
Optimize detection thresholds per transaction type, reduce false positives, tune velocity windows, calibrate ML model, improve graph analysis depth
- primitives
- 10
- waf
- 5
- industry
- general
- azure
- 64-ai-sales-assistantmediumOptimize scoring weights for conversion correlation, email personalization depth, talk track relevance, CRM sync frequency, cost per lead
Optimize scoring weights for conversion correlation, email personalization depth, talk track relevance, CRM sync frequency, cost per lead
- primitives
- 10
- waf
- 4
- industry
- general
- azure
- 66-ai-infrastructure-optimizermediumOptimize utilization thresholds, cost anomaly sensitivity, analysis frequency, auto-scale triggers, GPU-to-CPU migration criteria
Optimize utilization thresholds, cost anomaly sensitivity, analysis frequency, auto-scale triggers, GPU-to-CPU migration criteria
- primitives
- 10
- waf
- 5
- industry
- general
- azure
- 67-ai-knowledge-managementlargeOptimize capture rate from sources, dedup similarity threshold, taxonomy depth, freshness TTL, expertise scoring weights, retrieval relevance
Optimize capture rate from sources, dedup similarity threshold, taxonomy depth, freshness TTL, expertise scoring weights, retrieval relevance
- primitives
- 10
- waf
- 5
- industry
- general
- azure