My B2B company directory holds a large set of contact records, and right now all I have for each entry is a single-line street address (e.g., “123 Main St, Springfield, IL 62704, USA”). I need those addresses cleansed and validated so the file can reliably drive direct-mail campaigns, regional sales analysis, and CRM automations. Here is what I need done: • Parse every single-line address into standardized fields (street, city, state/province, postal code, country). • Verify each address against authoritative postal databases or reliable geocoding APIs, correcting misspellings and formatting along the way. • Flag any records that cannot be confidently validated so I can review them manually. • Deliver the cleaned data back to me in the same order, preferably as a CSV or Excel file, plus a brief summary report (total rows processed, rows corrected, rows flagged). A sound understanding of address-validation tools such as USPS, Canada Post, Royal Mail, Google Maps API, or similar services is essential, and any experience with bulk data cleaning in Python, R, or specialized software (OpenRefine, Melissa, Loqate, etc.) will help you move quickly. Accuracy matters more than speed; I will spot-check the output against live postal look-ups before sign-off. If something in my brief seems unclear, let me know early so we can keep the project moving smoothly.