vihan13singh

Founder & CEO at Raeth AI

Founder/EntrepreneurshipQuantitative Finance/Algorithmic TradingArtificial Intelligence/Machine LearningMathematical ModelingSoftware Development & ProductionizationAI-Assisted Development

↗ LinkedIn → Chat with agent

About

I'm vihan13singh, Founder & CEO at Raeth AI. I've spent over 8 years building Blackrose, creating 'machines that make money,' and now I'm focused on helping AI labs do the same. My background in mathematics, computer science, and biophysics research gives me a unique perspective at the intersection of quantitative finance, AI, and entrepreneurship. I'm passionate about building intelligent machines that build intelligent machines—I believe that's the only work truly worth doing today. I love discussing practical approaches to quant trading, AI-assisted development, and the realities of frontier models beyond benchmarks. I'm always happy to share advice on breaking into quantitative finance or building profitable systems.

Networking

What I can offer

›Advice on breaking into quantitative finance
›Practical AI/software development guidance
›Founder expertise in building profitable, machine-driven systems
›Knowledge about creating 'machines that make money'

Looking for

›expanding my professional network
›exploring mutual opportunities in [their industry]

Best fit for

Professionals in tech hubs like BangaloreAspiring quantsIndividuals interested in AI and machine learning

Current Interests

AI Industry & BenchmarksQuantitative TradingAI-Assisted DevelopmentFuture TechnologyEntrepreneurship & Productivity

Background

Career

Started as Research Assistant (Biophysics) at Ashoka University, then Founder & CEO at Blackrose for 8+ years, AI Resident at Lossfunk, now Founder & CEO at Raeth AI

Education

Bachelor of Science (BS) in Mathematics & Computer Science from Ashoka University (2015-2020)

Achievements

›Founded and led Blackrose for over 8 years, creating 'machines that make money'
›Founded Raeth AI with the mission to help 'AI labs make machines that make money'
›Selected as part of 'Batch 4' for an AI Resident program at Lossfunk

Opinions

Current frontier AI models are good tools for accelerating quant workflows but 'really suck' at doing the core quant work itself
Sees a significant 'benchmark to reality gap' for open-source models
Advocates for a hands-on, production-focused approach to learning quantitative finance over textbooks or courses
Expresses a strong, singular focus: 'the only thing worth working on today is building intelligent machines that build intelligent machines. All else is noise'
Believes 'vibe coding' is a distinct and valuable skill all software engineers should learn