The Recommendation Engine for Commodity Traders — Anekha Sokhal, Moshi

Anika, a founder with a background in trading and data, shares insights from her recent experience at the AI Engineers conference in New York. Originally from the UK, she transitioned from a successful career in energy derivatives trading at JP Morgan to entrepreneurship, driven by her passion for data and technology. Anika discusses the overwhelming pressure faced by AI engineers today, who are often expected to perform the roles of entire teams alone, reflecting a significant shift in workplace dynamics.

At the conference, Anika presents her startup, Moshi, which aims to provide real-time insights for financial traders by processing vast amounts of data. She explains how Moshi analyzes both structured and unstructured data, including news and alternative data sources, to deliver critical information to traders. Anika emphasizes the importance of filtering relevant data and integrating user-specific information to enhance trading decisions.

The conversation also touches on the challenges of engaging potential clients and the need for effective communication in the finance sector. Anika notes the high interest in her presentation, leading to numerous follow-up meetings with traders and AI engineers. She expresses the desire for more efficient networking opportunities at conferences, suggesting that structured group meetings could facilitate better connections among attendees.

Anekha Sokhal, CEO of Moshi, joins swyx to discuss building a recommendation engine for commodity traders, turning market data into useful signals, and designing AI that fits users’ workflows. Watch: YouTube · Moshi · Anekha 0:00 AI Engineer New York a...