Siddhant Masson is the CEO and Co-Founder of Wokelo AI, a generative AI platform transforming how investment research is conducted across private markets. He leads the vision and strategy behind Wokelo’s purpose-built research agent, which enables firms to automate complex research workflows – from due diligence and sector analysis to portfolio monitoring – with speed, structure, and precision.

Wokelo started in 2023 and is already being used by many well-known firms across the industry. It’s also the only platform in its space that’s backed by a strategic investor.

In investment research specifically, we’re going to see AI go from being a helpful add-on to something that’s deeply embedded in decision-making.

With a background in corporate development and M&A at Deloitte and the Tata Group, Siddhant brings deep expertise in financial research and strategy execution. His goal with Wokelo is to make high-quality insights easier to access, faster to produce, and usable in real time.

What inspired you to build Wokelo AI?

The concept for Wokelo came directly from my own experience. While working in management consulting at Deloitte, I saw firsthand how much time was lost to manual, repetitive tasks. Endless desk research, limited data on private companies, and underutilized insights made the process not only inefficient but mentally exhausting. The way research was being done wasn’t built for the pace or complexity of modern decision-making.

Later, while pursuing a Master’s in Applied Machine Learning and NLP, I began experimenting with large language models and built a prototype to automate some of the core research workflows I used to handle manually. It turned out to be faster, more consistent, and surprisingly robust. So that was actually the turning point. I realized this could be a foundation for something much bigger. Wokelo was born from that intersection of lived pain points and real technical possibilities.

What specific problem does Wokelo solve for investment teams today?

Wokelo removes one of the biggest bottlenecks in the research process. Traditional research, even for basic fact packs, can take up to 2–3 days, but the platform can pull together these insights in under 30 minutes. Wokelo scans over 100,000 real-time sources and distills everything into clear, well-structured presentations ready to use across investment organizations. In high-stakes investment environments, speed and depth are often at odds – you either get something fast or something thorough. Wokelo bridges that gap and automates the heavy lifting behind research, so teams can spend less time compiling and more time interpreting, strategizing, and ultimately making better decisions.

What types of organizations are using Wokelo today?

We work with a broad range of organizations that rely heavily on market intelligence – global consulting firms, private equity funds, corporate strategy teams, and venture groups. What unites these teams is the need to move quickly and operate effectively in a fast-changing industry. They need fresh, data-backed insights at their fingertips to make confident decisions without getting bogged down in research cycles. That’s why Wokelo is quickly becoming their go-to platform. They use the platform for due diligence, sector scans, portfolio monitoring, so basically any scenario where fast, structured insight is mission-critical.

What’s the measurable impact firms have seen since using Wokelo?

One of our Big Four clients recently reported saving over 3,600 analyst hours in just a few months of using the platform. They cut research turnaround time by 75% – a major shift in an industry where consultants often work 70+ hour weeks. They’ve used Wokelo for Day-0 fact packs, proposal development, and market intelligence, generating more than 900 reports to date. A private equity firm also reported a 6x return on investment. Across the board, we’ve helped clients increase their deal-screening volume simply by removing the bottlenecks that slow down early-stage research.

You’re working at the intersection of AI and finance — what fundamental shifts are you seeing in how financial research and decision-making are evolving because of AI?

We’re watching research evolve from something static and retrospective to something continuous and predictive. AI is making it possible to monitor markets, sectors, and companies in real time – not just react to news, but anticipate where things are heading. In finance, that’s a game-changer. It means being able to catch subtle but meaningful signals like emerging themes in regulatory filings, changes in leadership activity, or momentum building around a specific technology long before they hit the headlines. AI is also democratizing access to that kind of insight, so smaller firms can now operate with the same intelligence muscle as the giants.

How should business leaders think about adopting AI in such high-stakes environments?

I think that amid all this hype around AI, the smartest approach is to focus on where AI can actually move the needle. The best AI use cases are practical. In high-stakes environments, leaders should be asking: where are my smartest people spending time on tasks that don’t require their full brainpower, and whether there’s a smarter way to handle that work? That’s your AI opportunity. When used well, AI becomes a strategic enabler. The key is to stop thinking of AI as a magic fix and start seeing it as a force multiplier – something that makes your best people even more effective and lets them focus on the high-impact stuff, while reducing inefficiencies across the board.

What’s your take on hallucinations and trust in AI-generated content?

It’s a real issue and one we’ve addressed head-on. Every report Wokelo generates references 200+ sources, processes over 2,000 AI prompts, and uses 50+ micro-agents to synthesize complex data into sharp, actionable intelligence. And yes, hallucinations do happen, which is why we built a second layer of fact-checking into the system using an independent model that verifies whether each insight actually appears in the source material. Every output is citation-backed and fully traceable. If a statement is in the report, the source is a click away. That level of transparency is essential in finance because no one’s going to make a $100 million decision based on a guess.

How do you think AI will reshape private markets in the next 3–5 years?

Private markets have always been difficult to analyze at scale. Over the next few years, AI will fundamentally shift how private market research is done by bringing structure, speed, and scale to a space that’s historically been opaque.

We’ll see diligence cycles compress from weeks to days, as AI tools surface relevant insights from filings, partnerships, product updates, and other hard-to-track signals – all in real time. It will also become easier to monitor entire sectors, not just individual companies. That kind of broader visibility means investors can pick up on shifts earlier and act with more confidence. We’re already seeing firms make decisions with more context and less delay. Over time, this kind of speed and insight will raise the bar in private markets. We’ll see more competition, more informed decisions, and a faster pace of execution, especially for firms willing to integrate AI into their core workflows.

What excites you most about the future of AI in this space?

We’re moving past the novelty phase, and that is what excites me most. The early question was: can AI do this? Now, the better question is: how do we build real workflows around it?

In investment research specifically, we’re going to see AI go from being a helpful add-on to something that’s deeply embedded in decision-making. I’m excited about a future where analysts can move faster, spot patterns earlier, and spend more of their time thinking strategically – not digging through data. The tools are getting smarter, but more importantly, the people using them are getting more sophisticated about how to use them. That combination is where things really get interesting.

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