I need an AI-driven agent that ingests raw numerical datasets and instantly turns them into clear visual stories while surfacing the underlying patterns I might miss at first glance. The core goal is data analysis, so everything you build should revolve around extracting, interpreting, and presenting insights—not just crunching numbers. Here’s what I expect the agent to handle: • Data visualization: generate interactive charts and dashboards that allow me to slice, filter, and export results without touching code. • Pattern recognition: automatically detect correlations, trends, anomalies, and recurring motifs, flagging anything statistically significant and explaining why it matters. Python is my natural choice for this project, so feel free to lean on pandas, NumPy, scikit-learn, and visualization libraries such as Plotly or Matplotlib. If you can enhance pattern recognition with TensorFlow or PyTorch models, great—just keep the solution maintainable and well-documented. Deliverables will include: 1. Source code with clear instructions to reproduce results on my machine. 2. A one-click (or command) routine that feeds the agent new datasets and refreshes visual outputs. 3. A short report or notebook explaining the detected patterns and how the agent found them. Clean, commented code and concise documentation will be the yardstick for acceptance. I’m open to suggestions on architecture or tooling that make the agent faster and more reliable, so let me know what you need to get started.