Email Parser

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Mojo Case Study

Problem Statement

A global leader in ship broking needs a robust solution to efficiently identify and classify over 2 million emails daily into various categories. The solution must offer real-time parsing and data extraction while maintaining an accuracy rate above 95%. search engine sites for the UK and Europe. The challenge lies in efficiently discovering and aggregating job postings while ensuring data accuracy and reliability.

Our solution

Email Identification and Classification: Implement a machine learning model to identify and categorize emails into multiple predefined categories, ensuring efficient sorting and organization.
Real-Time Parsing: Utilize advanced parsing techniques to process and extract data from emails in real-time, enabling timely access to critical information.
High Accuracy: Achieve an accuracy rate of over 95% in email classification and data extraction, ensuring reliable and precise results.
Scalable Processing: Design the system to handle the processing of up to 2 million emails daily, ensuring scalability and performance under high-volume conditions.
Continuous Improvement: Integrate mechanisms for ongoing model training and refinement to adapt to evolving email patterns and improve classification accuracy over time.

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Benefits

Efficient Email Management: Automated classification of emails into multiple categories enhances organization and retrieval, reducing manual sorting efforts.
Timely Data Access: Immediate parsing and data extraction provide prompt access to important information, facilitating faster decision-making.
High Reliability: Consistently achieving over 95% accuracy ensures dependable classification and data extraction, minimizing errors and inaccuracies.
Scalable Solution: The system’s ability to manage up to 2 million emails daily supports large-scale operations and maintains performance during peak loads.