A distinguished figure in this field is Shreekant Mandvikar, an IPA researcher, practitioner, and mentor with over 14 years of experience. His academic background includes a Bachelor of Engineering in Information Technology from RGPV and a Postgraduate Degree in Artificial Intelligence and Machine Learning from The University of Texas at Austin. Shreekant’s expertise lies in automating business processes through intelligent methods, and his research, particularly on Generative AI and RPA indexing, has gained international recognition. His career trajectory, marked by his tenure at a major IT conglomerate present in 46 countries, reflects his profound impact on the sector.

Shreekant’s career is replete with significant achievements. As a Principal Automation Engineer, he developed innovative solutions that revolutionized industries such as banking, healthcare, travel, and communications. A notable accomplishment is his automated solution transforming mainframe macros into RPA, which clinched a $45 million contract. This solution enabled a seamless transition from mainframe to Java applications without necessitating end-user change management, thereby averting potential innovation and growth stagnation.

Additionally, Shreekant spearheaded a project for a leading US Pharmacy Chain, integrating RPA with cognitive technologies. This innovation boosted efficiency, leading to a 250-350% annual return on investment and saving significant time per customer per prescription. The project benefited over 50,000 customers and resulted in a collective time saving of 4,500 hours.

His proficiency also extends to finance and accounting automation. He developed a solution for an online travel ticketing aggregator, yielding a 300% return on investment and speeding up month-end closure activities. This success attracted World’s largest travel company as a new client and secured a significant two-year contract. Shreekant also played a crucial role in automating processes for a Chicago newspaper, leading to faster month-end and quarter-end closures.

Shreekant’s approach to client engagement is noteworthy. He assists clients in their initial automation stages, using his company’s proprietary framework to evaluate automation products, identify appropriate use cases, and ensure solutions meet both current and future needs.

Beyond his professional accomplishments, Shreekant is a seasoned mentor, having trained over 120 associates in automation. He  is invited to industry podcasts conducted by AAITP– “Build Your First Bot” and “How Data is Transforming Technology.” Participates as a judge in hackathons like hackHARVARD and hackMIT. His expertise is also recognized in his role as a panelist for the GLOBEE awards.

He has contributed significantly to academic research, with notable publications including:

1. “Augmenting Intelligent Document Processing (IDP) Workflows with Contemporary Large Language Models (LLMs)” (Oct 2023) – Discussing the integration of LLMs in IDP workflows.
2. “Process Automation 2.0 with Generative AI Framework” (Oct 2023) – Presenting an advanced AI framework for enhancing organizational efficiency.
3. “Factors to Consider When Selecting a Large Language Model: A Comparative Analysis” (Aug 2023) – Analyzing key factors in selecting LLMs for organizations.
4. “Indexing Robotic Process Automation Products” (Aug 2023) – Discussing criteria for selecting the best RPA products based on objective data and testing.

Shreekant’s contributions have earned him significant recognition, including the LinkedIn Top Process Automation Voice award in 2023. He is also a recipient of the 13th Globee Business Awards (Silver in Robotic Process Automation) and the 15th Golden Bridge Awards.

Shreekant Mandvikar’s journey in Intelligent Process Automation is a testament to the transformative power of expertise, innovation, and dedication. His extensive skills and significant contributions continuously redefine the automation landscape, setting a standard for industry professionals and shaping the future of IPA in the United States and globally.