Foram Jivani
About Foram Jivani
Foram Jivani is a Software Engineer with expertise in document processing and information extraction, currently working at Searce Inc in Bengaluru. He has a background in developing algorithms that enhance document onboarding efficiency and has experience with major Indian insurance clients.
Current Role at Searce Inc
Foram Jivani currently serves as a Software Engineer at Searce Inc, a position she has held since 2019. Based in the Bengaluru Area, she focuses on developing innovative solutions for document processing. Her work includes delivering end-to-end proofs of concept (POCs) and onboarding documents for major Indian insurance clients, specifically in the lending sector. She has contributed to the onboarding of various lending documents from North America, such as Closing Disclosure and W2 Forms, onto Recognic.AI.
Education and Expertise
Foram Jivani holds a Master of Technology (MTech) degree in Information and Communication Technology from Dhirubhai Ambani Institute of Information and Communication Technology, where she studied from 2017 to 2019. Prior to that, she earned a Bachelor of Technology (BTech) in Computer Science and Engineering from the Institute of Technology, Nirma University, from 2009 to 2013. Her educational background provides a strong foundation for her expertise in software engineering and document processing technologies.
Professional Background
Foram Jivani has a diverse professional background in software engineering and technology. She began her career at Cognizant, where she worked as a Programmer Analyst Trainee from 2013 to 2014 and later as a Programmer Analyst from 2014 to 2015 in Pune Area, India. After her tenure at Cognizant, she served as a Teaching Assistant at Dhirubhai Ambani Institute of Information and Communication Technology for one year, from 2017 to 2018. She also completed a five-month internship at Searce Inc in 2019 before transitioning to her current role.
Technical Achievements
Foram Jivani has made significant contributions to document processing technologies. She developed a YOLOv5 Object detection algorithm that reduced inference time from 20 seconds to 5 seconds per document. Additionally, she conceptualized a signal processing-based algorithm that achieved production-level accuracies in document processing using Google Vision OCR. Her work also includes developing an end-to-end key information extraction API that significantly reduced document onboarding time from months to days.
Projects and Innovations
Throughout her career, Foram Jivani has been involved in various projects that showcase her skills in document processing. She achieved state-of-the-art performance using a Graph Convolutional Network (GCN)-based extraction algorithm for documents with multiple templates, including bank statements and invoices. Her ability to deliver end-to-end POCs and onboarding documents demonstrates her commitment to innovation in the field of software engineering.