Play 87 β Dynamic Pricing Engine π°
AI dynamic pricing β demand-based optimization, competitor monitoring, elasticity modeling, A/B testing, fairness-constrained pricing.
Build a dynamic pricing engine. ML elasticity models predict demand sensitivity, scipy optimization finds revenue-maximizing prices within fairness constraints (margin floor, change caps, no demographic discrimination), competitor monitoring maintains market positioning, and A/B testing validates price points with statistical significance.
Quick Start
cd solution-plays/87-dynamic-pricing-engine
az deployment group create -g $RG -f infra/main.bicep -p infra/parameters.json
code .
# Use @builder to implement, @reviewer to audit, @tuner to optimizeArchitecture
π Full architecture details
Pre-Tuned Defaults
- Constraints: 15% min margin Β· Β±10% max daily change Β· 2Γ surge cap Β· no demographic pricing
- Elasticity: Gradient boosting Β· 10 features Β· weekly retrain Β· cross-elasticity enabled
- Optimization: Revenue 60% / margin 40% Β· hourly updates Β· 0.7 dampening
- A/B: 1000 min samples Β· 95% confidence Β· 14-day max duration
DevKit (AI-Assisted Development)
| Primitive | What It Does |
|---|---|
agent.md | Root orchestrator with builderβreviewerβtuner handoffs |
copilot-instructions.md | Pricing domain (elasticity, fairness, A/B testing, surge caps) |
| 3 agents | Builder (gpt-4o), Reviewer (gpt-4o-mini), Tuner (gpt-4o-mini) |
| 3 skills | Deploy (215+ lines), Evaluate (120+ lines), Tune (240+ lines) |
| 4 prompts | /deploy, /test, /review, /evaluate with agent routing |
Cost Estimate
| Service | Dev/Test | Production | Enterprise |
|---|---|---|---|
| Azure OpenAI | $30 (PAYG) | $400 (PAYG) | $1,500 (PTU Reserved) |
| Azure Event Hubs | $12 (Basic) | $200 (Standard) | $750 (Premium) |
| Cosmos DB | $5 (Serverless) | $180 (3000 RU/s) | $600 (10000 RU/s) |
| Azure Cache for Redis | $15 (Basic C0) | $150 (Standard C2) | $500 (Enterprise E10) |
| Azure Machine Learning | $15 (Basic) | $300 (Standard) | $900 (Standard GPU) |
| Container Apps | $10 (Consumption) | $200 (Dedicated) | $550 (Dedicated HA) |
| Key Vault | $1 (Standard) | $8 (Standard) | $25 (Premium HSM) |
| Application Insights | $0 (Free) | $45 (Pay-per-GB) | $150 (Pay-per-GB) |
| Total | $88/mo | $1,483/mo | $4,975/mo |
π° Full cost breakdown
vs. Play 14 (Cost-Optimized AI Gateway)
| Aspect | Play 14 | Play 87 |
|---|---|---|
| Focus | AI service cost optimization | Product price optimization |
| Optimization | Model routing + caching | Elasticity + competitor positioning |
| Fairness | N/A | No demographic discrimination, surge caps |
| A/B Testing | N/A | Price point experimentation |
π Full documentation Β· π frootai.dev/solution-plays/87-dynamic-pricing-engineΒ Β· π¦ FAI Protocol
FAI Manifest
| Field | Value |
|---|---|
| Play | 87-dynamic-pricing-engine |
| Version | 1.0.0 |
| Knowledge | T3-Production-Patterns, O2-AI-Agents, F1-GenAI-Foundations |
| WAF Pillars | cost-optimization, performance-efficiency, reliability, responsible-ai |
Last updated on