Final-year Robotics & Automation Engineering student with a Minor in Computer Science & Engineering (Full Stack Development), focused on backend engineering, software architecture, and system design.
I build software by understanding problem constraints, data ownership, workload characteristics, and domain relationships before selecting technologies. My work spans backend systems, AI-powered retrieval, educational software, and structured knowledge platforms.
🌐 Portfolio: https://founder-portfolio.lgcsystems.xyz
Founder & Software Engineer — LGC Systems
LGC Systems (Learn. Govern. Construct.) is my long-term software engineering initiative focused on building systems that prioritize understanding, verification, scalability, and intentional architecture.
Every project begins with the same engineering approach:
- Understand the problem before selecting technology.
- Match architecture to workload and domain constraints.
- Design for maintainability, scalability, and clarity.
- Document engineering decisions alongside implementation.
A convention-over-configuration publishing platform where Markdown acts as the single source of truth, enabling automatic routing, metadata extraction, and dynamic content rendering through serverless APIs.
🔗 https://learn-with-linga.lgcsystems.xyz
Semantic bug retrieval system using Sentence Transformers, FAISS vector search, and similarity-based duplicate detection with clustering.
Repository: https://github.com/lingarobotics/bug-sense-ai
A backend system targeting reliable academic result delivery during university publication periods through scalable architecture, layered backend design, local caching, and concurrent request handling.
Repository: https://github.com/lingarobotics/ResultGrid
A concept-centered mathematics learning platform using relational knowledge modeling, reusable learning workflows, and curriculum-independent concept mapping.
Repository: https://github.com/lingarobotics/MathLogic
A repository intelligence platform that combines reusable frontend content with user-state analytics to support guided software architecture exploration.
Repository: https://github.com/lingarobotics/CodeBase-Insight
These projects focus on engineering learning, conceptual understanding, and professional development.
Concept verification through structured reasoning, teach-back validation, and understanding assessment.
🔗 https://concept-ai.lgcsystems.xyz
Programming practice emphasizing execution flow, defensive thinking, and logical reasoning before syntax.
🔗 https://learn-logic-code.lgcsystems.xyz
Communication training platform inspired by Thirukkural, helping students improve technical articulation through structured scenarios.
🔗 https://articulate-devlang.lgcsystems.xyz
- Backend Engineering with Java & Spring Boot
- System Design & Software Architecture
- Concurrent Systems & Performance Engineering
- AI Retrieval Systems & Vector Search
- Domain-Driven Design
- Database Design & Relational Modeling
- Performance Measurement & Observability
The long-term LGC Systems roadmap includes:
- LGC Govern AI
- LGC Arbitration
- AcadOS
- Emergency Corridor System (Final-Year Interdisciplinary Project)
- CivicProof
- Know Your Rights
- Analyze the problem before choosing the technology.
- Prefer architecture driven by constraints instead of trends.
- Treat documentation as part of engineering.
- Build measurable systems that can be validated through evidence.
- Use AI to accelerate engineering—not replace engineering thinking.
📍 Chennai, Tamil Nadu, India
"Good software is not defined by the number of technologies it uses, but by how intentionally those technologies solve the problem."