Customer Success Spotlight: CloudQuant

At Intrinio, we are known for being a top provider of innovative financial data. Our powerful technology is paving the way for developers and large enterprises across the globe and is positively changing the way our dispersed financial sector operates. Intrinio’s advanced, reliable platform delivers premium data packages that allow innovators to build with a peace of mind.  

We are proud to collaborate with some of the most innovative and impactful entrepreneurs and businesses, and we’re delighted to showcase their leading-edge work in our blog. Intrinio's Customer Success Spotlight series will focus on a client that has used our powerful technology to build something revolutionary.

It’s a new month and we’re delighted to introduce our next Customer Spotlight, CloudQuant! CloudQuant, is a resourceful technology and alternative data platform that provides a variety of financial services, including empowering businesses with smart investment strategies, trading tools, and conventionalized data. We spoke to the CEO of CloudQuant, Morgan Slade, about the company’s biggest successes and challenges and why they ultimately chose to work with Intrinio.  

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Give us the elevator pitch for your company.

CloudQuant is an Alternative Data, Research, and Technology provider on a mission to deliver data solutions to global financial services and B2B clients. Our platform empowers organizations to realize the power of historical and streaming data. Thousands of high-value datasets are accessible directly to researchers through a single integration. CloudQuant’s data advisors and research team utilize artificial intelligence to sift through massive quantities of alternative data to locate valuable sources and provide clients with data intelligence, scouting, and analytics services. CloudQuant simplifies data engineering and delivers data in a production-ready format.

What is your professional background?

CloudQuant CEO Morgan Slade has over 20 years of experience as a portfolio manager, researcher, technologist, executive, and entrepreneur in the financial services industry. Prior to CloudQuant, he built quantitative trading businesses at some of the world’s largest Hedge Funds and Investment Banks. In the past, he served as a Portfolio Manager for both Citadel Investments and Carlson Capital, served as Global Head of Equity Trading for several of the largest high-frequency trading firms, and was head of statistical arbitrage at Merrill Lynch. Morgan is a recognized expert in prediction, machine learning, high-frequency trading, and autonomous market making, and is interested in the application of AI in quantitative and fundamental trading and investing. Morgan earned a BS and MS in Materials Science and Engineering from MIT.

What inspired you to start your company?

We saw a major need to accelerate data adoption and to simplify the process of integration, licensing, and signal search. Our team has solved the problem of how to use new datasets to find new investment opportunities using our data fabric which delivers data in a research-ready format paired with our AI research stack and decades of investment experience.

Our journey began when we were integrating our first alternative dataset into our investment firm’s trading and research platform. The process took us over six months to complete and our engineering team vowed to find a better way to integrate new datasets in minutes rather than months. This experience inspired us to completely revamp how we approached data integration and to develop our streaming and historical data fabric.

What have been your biggest challenges, and what did you learn from them?

As we first entered the data industry, our focus was on selling new alternative datasets. For many of the datasets, it was initially unclear how to use them to generate investment returns. We noticed that the institutional data buyers really needed us to tell them how to make money with these new datasets. We were selling raw data, but the buyers wanted to purchase production-ready solutions- more like investment signals based on the raw data. We call this the sugar vs. candy problem. It’s as if the standalone data provided by hundreds of data suppliers is the sugar, but the client actually wants to buy “candy.” That is where CloudQuant’s Research Team comes in. In addition to integrating and delivering data in a research-ready format, our researchers turn the raw data into candy using our AI tech stack. In a way, we had to go back to our roots as investment managers to find the solution to the sugar vs. candy problem in the data marketplace.

What have been your biggest successes?

CloudQuant’s biggest successes are all rooted in providing data recommendations, a superior data experience, and research guidance for our clientele. For example, many times we are introduced to a client who has been struggling with data integration for months or years either in edge or cloud compute situations and are failing to find the value out of data they have licensed. We provide a data fabric overlay to help span the mote between where data physically sits and the data-hungry applications that need the data. Our engineers are able to onboard the dataset and make it completely digestible and easy to pull into their own system. The relief our clients experience when they realize they no longer have to tackle their own data engineering is the best part of our customer experience. Our mission is to deliver data in an easy-to-use format that anyone can analyze- our biggest success is just that!

How do you set yourself apart from your competitors?

We believe CloudQuant is unique in its data, signal, and technology offering. CloudQuant has simplified the issue of lengthy data access and integration. We have cut down our clients’ time to access data by standardizing the legal process for data and compliance teams through our Master License Agreement, one line of code data delivery, and continued research + customer support through the whole process and into a license. The CloudQuant triad of data, research signals, and technology provide a wide range of solutions to institutional investors, consultants, and data scientists.

Why did you choose to work with Intrinio?

At CloudQuant, we have integrated over 14,000 datasets into our platform, and are very familiar with leading data sources. Intrinio is a leader and innovator in modern data technologies and a very unique source that we were eager to partner with. They are a market leader at providing valuable and innovative data sources at a great price. Not to mention their NLP tech stack enables them to create high-quality document-based datasets to bridge the divide between the rapidly growing corpus of text-based information and structured data for researchers. They are at the forefront of innovation and turning unanalyzed information into high-quality actionable data. We view Intrinio as a valuable partner that will be instrumental to the data industry’s progression, and we are excited to be along for the ride. It covers the different ways you can access market data, how licenses and fees work, and where you can buy market data.

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