Ahmedabad, Gujarat, India
I work with high earners, IT professionals, and business leaders to help them structure life insurance and protection plans with clarity and long-term intent. My approach is advisory-led and documentation-focused. I help clients understand coverage needs, policy structure, and long-term implications before decisions are made. The focus is on risk coverage, continuity planning, and suitability — not product pushing. In addition to client-facing advisory work, I am also involved in independent, document-based review initiatives that emphasize scope clarity, data discipline, and written outcomes. Areas of focus: • Term and protection planning for high earners • Coverage structuring for IT leaders and CXOs • Risk continuity and family protection strategy • Documentation-led advisory processes I believe good financial decisions come from understanding, not urgency.
Most math tools either know the answer or explain their thinking. Rarely both. And almost none of them tell you when they're wrong. That's the problem I've been obsessed with solving. I'm building MathCore — an AI-driven mathematical intelligence system that solves, verifies, and explains math problems with genuine precision. Not just a calculator. Not just a chatbot that "does math." A system that actually checks its own reasoning and holds itself accountable. Here's what I kept seeing in the market: Symbolic engines like Wolfram Alpha are powerful, but they're rigid. They can't reason flexibly. LLM-based tools are flexible, but they hallucinate — confidently giving wrong answers with no way to catch themselves. Nobody had closed that gap: correctness + reasoning transparency + adaptability, all in one system. MathCore is my attempt to close it. Under the hood, it runs a multi-layer validation architecture — meaning outputs get rechecked across modules before they reach the user. I've built 70+ specialized math modules, each handling a specific domain: algebra, calculus, number theory, and more. Each one is independently testable and replaceable. One of the things I'm most proud of is the failure-aware design. The system doesn't just fail silently. It detects when something's wrong, flags it, and — through a credit-based trust model — actually compensates users when it can't deliver a reliable answer. That's a level of accountability you almost never see in AI tools. The short-term goal is simple: build the most reliable math-solving system available online. The mid-term goal is to become the trusted backend for math computation across EdTech platforms, research tools, and developer APIs. The long-term vision? A Mathematical Operating System — a foundational layer where AI doesn't just generate answers, it proves, verifies, and audits its reasoning. If you're working in EdTech, AI infrastructure, or just think math deserves better tooling — I'd love to connect.
Life Insurance Advisor (Part-time) Tata AIA Life Insurance • Advisory support for term and protection-based life insurance • Focus on need analysis, documentation review, and policy understanding • Worked with salaried professionals and high-income individuals • Emphasis on suitability and long-term coverage alignment
• Advisory support for term and protection-based life insurance • Focus on need analysis, documentation review, and policy understanding • Worked with salaried professionals and high-income individuals • Emphasis on suitability and long-term coverage alignment
Independent Entrepreneur SW Works • Advisory-focused work across insurance planning, documentation review, and structured analysis • Client interaction with emphasis on clarity, suitability, and long-term planning • Experience in written communication, structured reviews, and process-driven outcomes