Sunny's Profound AI Rep
Sunny's view on primary research shows how he separates firsthand intelligence from secondary noise.

Sunny Sharma
Edges
Sunny builds investment intelligence by going directly to industry participants rather than relying solely on secondary sources. He designs outreach campaigns, talks to operators and supply chain partners, and synthesizes what he learns into structured findings that inform deal decisions. At InCred Capital, he ran a direct outreach campaign to data center operators across Canada and East Africa, mapping market dynamics, competitive positioning, and barriers to entry for the firm's deal pipeline. His approach is to start with the decision the research needs to support, identify the gaps that actually matter, and then go get the information that moves the needle. He distinguishes between what can be desked and what requires primary work. This pattern of going to the source, structuring the findings, and connecting them to investment decisions is consistent across his IB and PE research work.
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Sunny builds the foundational research layer that underpins investment decisions: company profiles, industry analysis, competitive benchmarking, and financial models that give deal teams the context they need to move forward. At TresVista, he built end-to-end research and financial modeling for a PE sell-side CIM, owning the company profile, industry sizing, and valuation sensitivities. His work maintained a five-out-of-five client feedback score across two audits. At InCred Capital, he supported end-to-end execution of a cross-border M&A transaction for a US-based AI real estate platform, contributing to the analytical and documentation work that advanced the deal. His approach is to structure the research around the decision it needs to support, ensuring that every component, from market sizing to competitive positioning, connects directly to the investment thesis.
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Sunny applies AI to investment research workflows to increase the speed and scale of research without sacrificing analytical depth. He designs the structured processes that allow AI to handle data gathering and screening tasks while human judgment handles quality validation. At Model ML, he designs AI-driven research workflows for PE and VC clients, leading the team in validating AI-generated outputs before they reach clients. His mandate is to reduce research lead times while maintaining the rigor that investment decisions require. His approach is to identify where AI can reliably accelerate research tasks, such as market mapping, competitive analysis, and company screening, and where human oversight remains essential. This combination of AI efficiency and analytical quality control is the core of his current work. This capability is increasingly relevant for investment research functions looking to move faster without adding headcount.
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Sunny Sharma
About Me
Sunny is an investment research analyst with experience spanning investment banking, PE research, and AI-enabled research workflows. He has worked across deal execution, primary market research, and structured research process design for clients in the PE and VC space.
He currently works as an AI Analyst at Model ML, designing AI-driven research workflows for PE and VC clients to accelerate investment research while maintaining analytical depth.
At InCred Capital, he worked as an Investment Banking Analyst on end-to-end M&A and fundraising transactions, including a cross-border deal for a US-based AI-enabled real estate underwriting platform. He also ran primary outreach to data center operators in Canada, gathering market intelligence on barriers to entry that informed the firm's deal pipeline.
At TresVista, he supported PE clients with IC preparation, pitch books, financial modeling, and CIM development, maintaining a five-out-of-five client feedback score across two audits.

Sunny Sharma
The most valuable investment insights come from conversations with operators, not from what's already been written about them.”
Sunny Sharma
On primary research