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."