My current agent database sits in a single CSV file that’s now riddled with gaps and obsolete contacts. I need a small AI-driven program that can do two things for me: 1. Locate a reliable email address for every real-estate agent listed, even when the field is blank or obviously outdated. 2. Check that each address is still valid—no hard bounces, no obvious spam traps. Once the script has finished its sweep, it should generate a clean, separate report (CSV is fine) that pairs every agent’s record with the newly found, fully-verified email. Please do not write back into the source file; I’ll handle the merge on my end. Feel free to use Python, pandas, OpenAI embeddings, Regex, Hunter.io, ZeroBounce or any other smart blend of scraping, NLP or API-based validation you’re comfortable with—speed and accuracy matter more to me than the particular toolkit. Key acceptance criteria: • Every email listed in the output must pass SMTP or equivalent real-time verification. • The report must keep each row’s original unique ID so I can match it quickly. • A short README or comments explaining how to rerun the script on fresh CSVs. That’s all the moving parts. If the solution is straightforward to run from a command line or simple GUI, even better, but the core need is the email identification and verification itself.