
1
1
India
1 year of experience
I’m a Computer Science undergraduate who enjoys building products, solving problems, and exploring how technology can create real impact. Over the past few years, I’ve gained experience through internships, freelance work, and independent projects across software development, backend systems, machine learning, automation, and scalable applications. I enjoy taking ideas from scratch and turning them into something useful and practical. I’ve worked on projects across areas like healthcare workflows, market intelligence, civic infrastructure, and content systems, and I’m currently building Editorial.io. Alongside this, I enjoy learning new technologies, experimenting, and continuously improving both technically and personally. Outside of the building, I enjoy problem-solving, exploring ideas, and working in environments where I can learn fast and contribute meaningfully. I’m always open to opportunities in software engineering, product development, AI, and research where I can collaborate, grow, and build impactful things.

Governance.AI is an agentic security and observability platform designed for autonomous AI systems and multi-agent workflows. As AI agents become more integrated into real-world products, most systems still operate with very little visibility, monitoring, or governance. We wanted to build infrastructure that helps developers understand and control how AI systems behave internally. The platform introduces a centralized governance layer between users and AI agents. Instead of acting like a simple chatbot wrapper, Governance.AI continuously monitors workflows, traces execution paths, analyzes risky behavior, and enforces governance policies before actions are executed. Core capabilities include: Risk Detection & Prompt Analysis Policy Enforcement & Access Control Agent Monitoring & Observability Audit Trails & Explainability Red-Team Testing & Unsafe Prompt Detection Real-Time Governance Workflows The platform is built using a modular FastAPI service architecture connected through a scalable API gateway. We integrated LangSmith for tracing and observability, Auth0 for authentication, Neon PostgreSQL for infrastructure data, and a real enterprise-style dashboard with live workflows, analytics, traces, and governance events. Governance.AI can be integrated using: Python SDK REST APIs Gateway-based integrations Developers can test governance services directly from the dashboard, inspect traces, monitor workflows, and integrate Governance.AI into their own AI systems using SDKs or APIs. One important aspect of this project is that we intentionally avoided building a purely mocked prototype. Our focus was building a realistic developer infrastructure platform that could evolve into a production-grade governance layer for future AI ecosystems. We believe governance, trust, and observability will become foundational infrastructure for autonomous AI systems, similar to how monitoring and security became essential for cloud computing.
19 May 2026