Urgent.News

What's breaking now, across thousands of outlets.

AI

Nikkitha Shanker: From 3 years of UPSC prep to building a $2 million business

Nikkitha Shanker spent three years preparing for the UPSC Civil Services Examination before a startup experience redirected her career towards entrepreneurship. She founded Shoppre, which grew into a profitable e-commerce technology business generating about $2 million annually. Shanker later stepped away from the company to pursue AI, spending nearly a year experimenting before co-founding…

Nikkitha Shanker: From 3 years of UPSC prep to building a $2 million business

Nikkitha Shanker, born in Kerala and raised in the Middle East, initially planned to enter the civil services. She spent three years preparing for the UPSC Civil Services Examination. However, after failing to clear the examination, Shanker found herself drawn to the world of startups and technology. This shift in career direction led her to co-found SuperBryn, an AI startup focused on enhancing the reliability of voice agents.

SuperBryn has secured $1.2 million in funding from Kalaari Capital and angel investors, according to Shanker's account. Before embarking on this new venture, Shanker had built an e-commerce technology company that grew to an annual revenue of around $2 million and achieved profitability. After deciding to pursue artificial intelligence, Shanker stepped away from the day-to-day operations of her previous business, allowing her team to run it independently.

Today, Shanker balances her responsibilities between Bengaluru and San Francisco while leading SuperBryn.

Written by urgent.news from Times of India's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.

Read the original at timesofindia.indiatimes.com →

More in AI

VRAM for local LLMs: why memory bandwidth sets your tokens per second

How much VRAM for an LLM is the wrong first question. The better one is how fast that VRAM is, because a local model generating text reads its entire set of weights from memory for every single token.

  • Memory bandwidth, not VRAM size, determines LLM speed
  • Token generation requires reading all model weights from memory
  • RTX 3090's 936 GB/s bandwidth generates ~90 tokens/second

More from Wednesday 30 September →