Markets EQ

Welcome to the team Helios! The strategic purchase of the Helios voice tone AI platform supercharges our mission here at Markets EQ. This enables the most advanced understanding that any #generativeAI platform has in the capital markets. Period. Our vision is to usher in a new era of capital markets intelligence, where confidence and connection are the currencies that drive us forward, beyond the limitations of legacy systems. With Helios integrated by end of Q2, we are separating ourselves from those legacy systems for a tremendous second of 2024.

2024 is the year of voice 🚀

An absolute honor to be included with such an innovative group. Boston here we come!! 🌆

A big one for us to showcase the power of voice AI across asset management and corporate intelligence. Buy your tickets today for the November 13th event in NYC. Zeynep Yenisey will be on-site as well for anyone wanting to learn more about what EQ can offer.

We are pumped for the fall!

Love this and love the earnings call reference! The world of preparation is only becoming more important. For financial pros, you can achieve performance master with Markets EQ

I built my first startup at 18. (It got millions of downloads on Android) - It was exhilarating - I learned more than any class could teach - I was in way over my head But hey, I was young and hungry, so I dove in. Years later, I found myself at Spotify. Working on audio AI before it was cool. I remember sitting in meetings, thinking: "This is the future of how we'll interact with sound." I started dreaming of what else was possible. I wasn't just part of a company. I was part of a revolution. Fast forward to 2017, I founded Helios: - We created speech analytics for Wall Street - I had to learn everything about finance - I worked harder than ever before But I was building something that didn't exist before: 6 years later, that vision evolved into Markets EQ. Now we're using AI to decode the human voice in finance. Today: - We're partnering with Google Cloud - We're changing how investors analyze companies - We're working with some of the biggest names in finance It took me a decade to find my true calling. Countless sleepless nights to bring it to life. And now, we're just scratching the surface of what's possible. The rollercoaster never stops, but man, what a ride 🚀

💪🏼

I joined AI expert Aziz Lookman, Ph.D. and Capital One’s director of machine learning  Sonu Chopra-Khullar on a panel organized by moderator Nicole M. Allen from the LSEG (London Stock Exchange Group) to talk about how hedge funds are using large language models. My main takeaway was that the fascination on Wall Street with how the AI models work is giving way to a focus on what can be done with them. Also, as much as there is widespread agreement that generative AI is mind-bendingly revolutionary, larger companies are struggling to adopt it. Sonu made excellent points, notably to remind the audience not to think about Gen AI too narrowly. The technology will be applicable in arenas we aren’t even thinking about now. Aziz challenged the group to allocate some small amount of money to everyone at their firm to experiment with AI solutions. I talked about four startups that illustrate how AI is being used. Broadly, they are focused on summarization, text generation, model creation and text analysis. All address the practical issue of how to reduce time spent by analysts compiling and assessing information. DoTadda, Inc., a start up run by Andrew Meister, started out as a way to summarize and query transcripts, especially earnings conference calls. The company has added historical documents to enable analysts to ask more complex questions. I asked DoTadda this question: "What geographic area is Exxon showing the most interest in over the last 12 quarters and how is it changing?" The answer:  Guyana, The Permian Basin, Mozambique and Qatar. Pricing Culture, a startup run by Bhargav Shivarthy, is taking arcane, proprietary data sets to generate text, thereby making the information more accessible.  I used the system to tap into data assembled by Carbon Arc and generate a story about fluctuations in discretionary spending based on credit cards data. The big idea here is that most data sets only make sense to a small number of experts. Text, especially when context is included, makes it useful to a larger population of analysts. SigTech is a startup funded by Alan Howard that taps into AI to provide answers to complex scenarios, many of which would have previously required quants to answer. Yesterday, I asked the system: "What jobless claim number would justify a 50 basis point cut?"  It replied: "The answer is 450,000 or above combined with other eco weakness like jobless over 4.5%." It also provided historical context for the basis of making that determination. Markets EQ, co-founded by Sean Austin, captures earnings conference calls and other audio files to generate transcripts, summaries and analytics . Tone is important because studies have shown it accounts for as much as 38% of the information we communicate when we speak. The analytics include the speed of speech as well as  tone, which can indicate sentiment and stress at odds with the words someone is literally saying. 

For those in NYC this week, drop us a line for coffee!