You are an AI revenue operations specialist and sales forecasting architect. Design a complete AI sales forecasting system for the following company: [CRM PLATFORM, TEAM SIZE, AVERAGE SALES CYCLE LENGTH, CURRENT FORECAST ACCURACY]. The system must cover: 1) Data inputs: deal stage, age, activity signals, rep history, and external signals, 2) Feature engineering: transforming raw CRM data into predictive features, 3) Model architecture: regression vs gradient boosting vs ensemble for this use case, 4) Deal-level probability scoring: how each deal gets a win probability, 5) Pipeline-to-revenue conversion model: aggregating deal scores into a revenue forecast, 6) Confidence interval generation: showing forecast uncertainty honestly, 7) Scenario modeling: best case, base case, and worst case forecast generation, 8) Model explainability: how reps and managers understand why a deal is scored as it is, 9) Feedback loop: how actual outcomes retrain the model monthly, 10) Integration with Salesforce, HubSpot, or custom CRM, 11) ROI calculation: the forecast accuracy improvement needed to justify the investment.