Deepak Guneja is a BITS Pilani (Pilani, ’19) graduate in BE Computer Science with a minor in Finance. He is the co-founder of Plux, with an impressive background that includes roles at D.E. Shaw and Morgan Stanley, and academic credentials from London Business School. The idea behind Plux was to help financial professionals make sense of the overwhelming data they encounter every day. At Plux, he is addressing the challenge of unstructured data in finance, blending his deep knowledge of both technology and quantitative analysis to build solutions that streamline financial workflows.

Your career began in finance, but what first sparked your interest in this field? Did BITS Pilani have a role in shaping that interest?

I did not come from a finance background. I was not even familiar with economics until I took the Principles of Economics (POE) course at BITS Pilani. That course changed everything for me. It was the first time I studied something beyond the usual science and math (PCM). I enjoyed it so much that I went beyond the syllabus and became the course topper. From there, I decided to pursue a minor in finance, which eventually led to an internship at D.E. Shaw, where I gained exposure to the tech side of finance. BITS laid the foundation.

Apart from academics, how did your experience at BITS shape you as a person?

BITS was not just about studying, even though I took my academics seriously. I was also involved in debates, public speaking, and entrepreneurship. Additionally, I worked on building trading algorithms and connected with many people from the Quantopian community—a platform for quant enthusiasts. We even attempted to build a marketplace for small Kirana stores, though that did not materialize. These experiences helped me explore different domains and develop a diverse skill set, which I still rely on today.

You eventually shifted from a tech role to a quantitative analysis role in finance. How did that transition happen?

After my time at D.E. Shaw, I wanted to move into a role that combined both finance and technology. Initially, I was in a tech-heavy position, but I aspired to transition into a front-office role. So, when the opportunity for a quant role arose, I seized it. It was the perfect blend of the tools I had been working with and my growing interest in finance. It felt like a natural transition to a role that allowed me to work more with data and analysis.

What inspired you to build Plux, and what problem are you aiming to solve?

Plux was born out of a simple observation: finance professionals deal with enormous amounts of unstructured data. After interviewing around 100 people in the finance industry, we realized the scale of the problem. PDFs, reports, and other documents are all unstructured, and people are manually searching through them to find the information they need. Our goal with Plux is to automate this process, making it easier to extract insights and perform scenario analysis. We designed Plux to build relationships across documents and pre-process data to deliver more relevant answers. One book that greatly influenced my thinking on this was The Man Who Solved the Market by Gregory Zuckerman, which explores how data can be harnessed effectively.

Companies like Bloomberg have access to vast amounts of structured data. Does that make them a major competitor for Plux?

BloombergGPT exists, but it is not perfect. Many big players, like KKR, still handle tasks manually because their primary focus is on delivering value to their clients and managing core business operations. Building in-house solutions would be costly, time-consuming, and require immense focus. Our advantage lies in addressing the specific issue of unstructured data, allowing us to adapt quickly while they focus on their main strengths. Moreover, the Innovator’s Dilemma is real companies with established cash cows are often hesitant to explore new territories. Our strength is that we are dedicated to solving this problem with unstructured data, and we can adapt swiftly.

Data security is a major concern for many companies. How do you plan to address that with Plux?

Data security is a major concern, especially for larger clients. Smaller funds tend to be less worried about it, so we offer them a cloud-based solution. For bigger clients, who are much more cautious about data confidentiality, we provide an on-premise solution, allowing them to run our models within their infrastructure. This way, they maintain full control over their sensitive data while still benefiting from our technology.