Hey, I'm Jayansh Bagga.
I’m a Computer Science student at Western and Founder & Technical Lead of Savify, a privately-backed fintech startup. I build scalable systems across software, AI, and finance from LLM infrastructure to backend applications. I also believe that computer science students can take a cue from the finance world, sharp code deserves a sharp suit.
About Me
I’m a Computer Science student at Western University, building at the intersection of software, AI, and finance. I’ve been working on real-world systems—from LLM-based infrastructure to scalable backend applications. I’m especially interested in building products that are not just technically strong, but genuinely useful.
When I’m not coding, I’m usually expanding my vocabulary, picking up new languages, sampling colognes and cognac, or just touching grass to balance it all out.
Currently Working On
- Moving to Toronto to start my SWE internship at Flynn, working on enterprise systems and scaling real-world applications.
- Scaling The Savify app with a team of five; refining features, optimizing backend performance, and preparing for the next funding phase.
- Designing systems that learn, solving problems that hurt, and building toward what’s next under Project Kalson.
- Developing my personal brand and investment portfolio while pursuing bigger professional opportunities.
Projects
Savify is a privately-backed fintech platform focused on goal-based savings, combining machine learning insights, financial analytics, and gamified user engagement. Currently at 150+ registered users with a live platform and mobile app in development, scaling toward 500+ users post-launch.
Built a FastAPI semantic cache for Boardy ($8M AI startup) using vector embeddings and cosine similarity to reduce LLM calls by 60% and latency by 40%. Designed as a modular caching engine for AI applications.
Reflecta is an AI-powered reflection system built during UofTHacks 13 that helps users analyze personal thoughts and writing using large language models. The project explores how AI can transform raw journaling into structured insights and pattern detection for self-awareness.
Education
B.Sc – Major in Computer Science
Skills
Work Timeline
Software Engineering Intern
Flynn Group of Companies
May 2026 - Sept 2026
AI Engineer
Outlier AI
Sept 2024 - May 2025
Data Analyst Intern
Carlo Romano
June 2024 - Sept 2024
Experiences
Software Engineering Intern
Flynn Group of Companies • May 2026 - Sept 2026
- Scheduled for a 16-week software engineering internship at Flynn, working on internal enterprise applications using Angular, .NET Core, and SQL.
- Contributing to backend services and API development, focusing on scalable systems and performance.
- Working with AWS and Azure DevOps pipelines to deploy and maintain production applications.
AI Engineer (LLM Systems)
Outlier AI • Sept 2024 - May 2025
- Engineered and optimized LLM-based systems using OpenAI APIs and Python, improving output accuracy by ~10–15% across production use cases.
- Built evaluation pipelines with Python and Pandas, benchmarking performance across 1K–5K+ model outputs.
- Scaled NLP workflows on 10K+ text records, supporting enterprise AI deployments and supervised learning tasks.
Data Analyst Intern
Carlo Romano • June 2024 - Sept 2024
- Built Python and SQL data pipelines to automate user experience and feedback validation across cross-regional operations.
- Engineered NLP workflows (NLTK, Pandas) to analyze 20,000+ customer records, enabling scalable sentiment analysis.
- Collaborated across India & Italy in agile workflows, participating in standups and sprint planning to deliver data-driven insights.