Pavanesh Gogineni

I’m an award-winning Computer Science B.Tech student and patent holder focused on AI-driven problem solving and backend automation. I’ve built business-ready solutions with AI APIs and LLMs, delivering up to 30% reduction in manual effort through practical workflows and strong model evaluation. My work has earned national recognition, including INAE IMP 2025 (1st place) and a published patent for an AI-driven precision agriculture system using computer vision.

Through internships, I’ve translated models and data into reliable systems. As a Full Stack Developer Intern at RedRietor, I engineered backend modules and REST APIs, improved response efficiency by 20%, managed structured data pipelines, and resolved critical production issues to strengthen overall reliability. As a Technical Analyst Intern at Rise Margin, I built 3+ automated reporting tools, cutting manual processing time by 30%, and delivered dashboards for executive reporting after analyzing 1,000+ records.

I enjoy turning messy data into decisions—whether it’s training and optimizing computer vision models (reaching 89.99% accuracy) or designing dashboards from real-time signals. I lead projects with a strong problem-solving mindset, and I’m especially drawn to roles where prompt engineering, backend systems, and data workflows work together to produce measurable results.