With efficiency being a driving force in today’s ecommerce, emails have become a major form of communication. However, deciphering information from these emails has been a be-labored task. With every email containing proprietary information, handling this information has become an arduous task that requires money, time and effort. To tackle this ecommerce problem, a computerized solution is important to expedite the extraction of information. In this paper, we have applied Named Entity Recognition, different rules and algorithms to extract important information from emails. The proposed solution tackles challenges revolving around tabular and natural language formats, which are the largest formats used for email communication. Use of this solution makes business easier to navigate through a variety of attachments: PDF, Word, and Excel. The proposed application has been applied on a dataset supplied by a Transportation company by which the results have been captured.