Pranav
Pradhan
I’m Pranav Pradhan, an engineer and builder focused on developing intelligent systems that bridge data, AI, and automation. My experience spans data engineering, machine learning, and robotics, where I’ve built distributed data pipelines for fintech companies and designed autonomous systems capable of real-time perception and navigation. I’m interested in creating technology that is both technically rigorous and genuinely useful.
At the moment, I’m building Fundsy, an AI-driven platform that simplifies how organizations access non-dilutive funding. Fundsy uses generative models to match startups, researchers, and nonprofits with the right grants and help them craft stronger applications. My work centers on making complex systems more accessible, scalable, and impactful through thoughtful engineering and design.
- Education
- BASc Mechatronics EngineeringSep 2020 – Jun 2025
- Current Role
- Co-Founder & EngineerFundsy AI
- Focus
- Applied AI, scalable data systems, and intelligent product development
- Location
- Toronto, Canada
Expertise
- Software Engineering
- Machine Learning
- Distributed Data Systems
- Cloud Computing
- Data Engineering
- Product Strategy
Previously @ Interac, Questrade, Stacktics, Healthcare Systems R&A
Always open to collaborations that blend product thinking with robust data foundations.
Work Experience
Building Fundsy, an AI-driven grant sourcing and application platform helping teams discover and win funding opportunities faster. Fundsy uses generative AI to match startups, researchers, and nonprofits with relevant grants, and helps them draft compelling proposals in minutes.
Worked on modernizing financial data systems, building services to automate fraud detection for E-transfer transactions. Improved reliability and efficiency across data pipelines using tools like FastAPI, Spark, and cloud technologies.
Helped scale data infrastructure by migrating large volumes of market data to the cloud. Improved data access speeds and helped build better reporting systems by optimizing queries and designing effective data models.
Developed real-time data pipelines using Google Cloud tools (Pub/Sub, Dataflow, BigQuery) to process and analyze user interaction data. Built and deployed machine learning models to forecast customer conversions and ad performance, helping clients improve return on ad spend.
Led the development of machine learning models for medical image analysis, improving diagnostic accuracy by 35%. Implemented automated CI/CD pipelines for model training and deployment across cloud platforms.
Featured Projects
Selected projects showcasing my work across AI systems, scalable data infrastructure, and full-stack product development.
