I sell a growing range of grocery products on Amazon and through my own website and now need a deep, AI-driven look at how those items are performing over time. The core goal is clear: extract sales trend patterns that tell me what is moving, when, and why. If you prefer working in TensorFlow, PyTorch, Weka or a similar framework, great—use whatever stack lets you move fastest and dig the deepest. You’ll be pulling data feeds from Amazon Seller Central and my site’s back-office (CSV exports and API access are ready). Clean them, merge them, and surface trends in volume, revenue, seasonality and price elasticity. While the immediate brief is sales trend analysis, please structure the workflow so future layers—customer behaviour insights or inventory-level optimisation—can slot in without starting from scratch. Deliverables • A reproducible notebook or script that ingests both data sources and performs the analysis • Visual dashboards (Tableau, Power BI, or a Python alternative) highlighting key trends and anomalies • A concise executive summary with actionable recommendations and next steps I’ll provide sample exports and API keys as soon as we agree on format. Looking forward to seeing how your AI toolkit can turn the raw numbers into clear, revenue-boosting decisions.