You are the Team — Anekha Sokhal, Moshi
Latent Space Latent.Space ● Covered by 2 sources
Moshi is building a trader copilot that turns market noise into what matters now. Its pitch is Bloomberg plus Claude plus Netflix, aimed at people drowning in data.
Based on reporting by Latent Space, Latent.Space — read the original for the full story.
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Anekha Sokhal is building the tool she wished she had on a trading desk. As CEO of Moshi, she wants software that connects market information to a trader’s book in real time, starting with commodity, energy and macro markets. The company’s pitch is simple enough, even if the machinery behind it is not: process more data than a person can read, then surface the bits that matter.
Sokhal’s path runs from mathematics at Warwick to energy derivatives at JPMorgan, where she started on emerging markets and later moved into commodities. She says she was always drawn to data-heavy work and to breaking markets down into their parts. That background shaped Moshi’s product thinking. Instead of a generic dashboard, she talks about a system that follows how traders actually work, including the trusted analysts, subscriptions and internal data they already rely on.
The scale she describes is brisk. In the time it takes her to say a sentence, Moshi has “learned 300 new things,” she says. The company mixes structured market data, fundamentals, news and other unstructured sources such as X and podcasts, then layers in a user’s private data. After cleaning, transformation, statistics and machine learning, it feeds that into what she calls an n-dimensional graph and pushes relevant output back to the user.
She doesn’t love the “new Bloomberg” label. Bloomberg is part of the picture, she says, but Moshi is closer to a blend of Bloomberg, Claude and Netflix: market data, an interface for working with it, and a recommendation engine that connects second- and third-order effects traders might otherwise miss. That recommendation layer is the real bet here. Not another dashboard, but software that pushes the next useful thing before the user goes hunting for it.
Sokhal also ties the product to a broader shift in AI work: engineers are being told “you are the team,” while users still need tools that fit their actual workflow. That gap is where Moshi is aiming. And if that sounds unglamorous, it is. But boring workflow problems are often where the money lives.
My take — AI-written commentary, not fact-checked reporting
The industry keeps celebrating dashboards because they’re easy to demo and hard to love. Moshi is taking the less glamorous route: workflow, trust, and recommendations that arrive before the user starts spelunking through tabs like it’s a hobby. That’s the right bet, because “brain in a dashboard” is not a product, it’s a confession.
Read more about this at: Latent Space