Surya Sourav Parida

Engineered robust backend infrastructure for an existing WhatsApp CRM system, integrating merchant accounts via GraphQL to enhance data flow and system capabilities.

Fine-tuned a 150M-parameter BART-based LLM by independently designing and curating a comprehensive dataset (collection, pre-processing, labeling, augmentation), optimizing its performance for specific applications.

Developed a secure, scalable FastAPI (Python) backend service on a VPS, enabling seamless communication between merchant accounts and the deployed LLM.

Built an automated Auto-Campaigner system leveraging customer data to generate and dispatch targeted campaigns through the WhatsApp Business API, streamlining outreach efforts.

Contributed to a notable 40% increase in customer conversions by enhancing merchant satisfaction through Generative AI-driven automation within the WhatsApp CRM.

Collaborated closely with Java and IoT teams to architect a scalable backend microservice for efficiently capturing and transmitting farmer-captured images.

Deployed a refined vision model on AWS SageMaker, ensuring seamless integration with the microservice for scalable cloud-based processing.

Developed and fine-tuned a CNN-based disease prediction model using an augmented plant leaf dataset to enhance prediction accuracy, achieving 97% accuracy with the Vision Model.

Designed and implemented a robust backend service for a multilingual FAQ system, enabling active translation into 6+ national languages and expanding user reach.

Enhanced system performance by leveraging Redis-based caching mechanisms, significantly reducing response times for critical operations.

Implemented efficient MongoDB querying and automatic cache invalidation on content updates, ensuring consistent data integrity and real-time information access.

Developed a comprehensive admin panel integrated with a WYSIWYG editor for streamlined FAQ management and rich text formatting, improving content update efficiency.