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Govind Chandrasekhar

AI Overview Search, as a Service | branch-ai.com | 2x YC Founder | ex-Twitter AI Lead

Govind Chandrasekhar is a highly accomplished individual in the field of technology and entrepreneurship.

With a strong educational background, Govind has studied Entrepreneurship at Y Combinator, Computer Engineering, and Entrepreneurship at the National University of Singapore, Technology Entrepreneurship at the University of Pennsylvania, among other programs.

He also holds a Graduate Certificate in Public Policy from The Takshashila Institution and completed his schooling at Dubai Modern High School.

Govind has had a diverse career path, holding key roles at various prestigious organizations.

He was the Co-Founder at Branch AI, Venture Partner at Pioneer Fund, and Machine Learning Engineering Manager at Twitter, showcasing his leadership and technical skills.

Govind is best known as the Co-Founder and Master of Search at semantics3, a successful startup that was part of Y Combinator's W13 batch.

His previous experiences include roles as a Software Engineer Intern at Quantum Inventions, Market Research Intern at Hand in Hand and Godrej Sara Lee Ltd., and Product Management at Altosoft Corporation.

Throughout his career, Govind Chandrasekhar has demonstrated a deep understanding of technology, entrepreneurship, and market research, making him a versatile and knowledgeable professional.

Highlights

Feb 19 · linkedin

The way we search is changing rapidly. For years, we’ve learnt to translate our thoughts into keywords, to make it easy for Google or Amazon to find the products we’re looking for. But in multiple conversations that I've recently had, insiders have told me about a doubling of their average query length and an increase in unique queries, quite likely a result of tools like ChatGPT & Perplexity encouraging us to search conversationally.

These changes have interesting second order effects:

  • Search becomes a tool for discovery & consideration, not just for looking up things we know exist
  • Longer queries become a rich source of user insights through unstructured data analysis
  • Content marketing can become more personalized as a result
  • Merchandising moves from tactics to strategy
  • Hyper-personalization on-site can finally become a reality
  • Incumbents are driven into a chicken-and-egg dilemma on whether to invest in AI
  • SEO & SEM undergo structural changes, as "popular keywords" reduce in market share

More in my article this week!

Feb 9 · linkedin

Last week, I wrote an article about why search tools are easy to setup, but difficult to tune for relevance.

This week, I dig into solutions! Specifically, the why and how of using LLMs (Large Language Models) as rankers. Rankers are a critical component of modern search engines, but are poorly adopted beyond the very large companies because of the investment and data overhead they entail.

LLMs enable up a more out-of-the-box and accessible approach that lets businesses improve their search without changing their search engines. (Disclaimer/context: BranchAI offers ecommerce LLM rankers via APIs that can be integrated with one line of code)

Govind Chandrasekhar
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Location

Bengaluru, Karnataka, India