Ektha's Profound AI Rep
Ektha builds investment conviction from first principles, from bottom-up TAM construction to high-signal expert sourcing.
Ektha S
Edges
Building Bottom-Up Market Analyses
Ektha builds market sizing analyses from first principles, starting with customer segments and geography before touching any top-down data. She defines the market boundary explicitly before measuring it, which keeps her estimates grounded rather than inflated. This pattern has shown up consistently in her work at D. E. Shaw, where she has built TAM analyses for Series A and B companies across cybersecurity and SaaS for the New York ventures desk. Her approach is to start with the customer: who they are, what geography they operate in, and what they are actually buying. She then builds pricing assumptions and validates the bottom-up figure against a top-down industry view. The output is a market sizing that the investment team can interrogate, not just accept.
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Sourcing High-Signal Expert Networks
Ektha identifies and sources industry experts who can genuinely opine on a specific company or sub-segment, not just generalists in a broader space. The quality of the expert is the output, not just the quantity of calls lined up. This has been a consistent part of her work at D. E. Shaw, where she sources experts for the ventures desk across cybersecurity and other sectors. The NY team runs the calls, but the quality of the expert she surfaces directly shapes what the team learns. In one case, a single expert call she sourced led the NY desk to drop a cybersecurity investment entirely. The expert's insights were strong enough to contradict the thesis the team had been building. The ability to find the right person for a specific question is a distinct research skill, and it is one she has developed through sustained practice at D. E. Shaw.
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India Market Pattern Recognition
Ektha has developed a formed view on how the Indian consumer and enterprise market differs from the US, built through sustained reading alongside her US-focused day job at D. E. Shaw. Her core observation is that in India, distribution and business model innovation tend to matter more than pure product quality. In the US, a clearly better product can find an established buyer persona and a willingness to pay. In India, the constraint is often whether the market is ready: whether customers have the budget, whether trust and adoption habits are in place, whether the distribution channel exists. This view has been built through newsletters, Substack, LinkedIn, and sector-specific research across fintech, SaaS, and deep tech. She tracks consumer behavior shifts and maps emerging opportunities across sectors she is not actively researching. The result is a perspective that shapes how she would approach investment evaluation in the Indian market: starting with distribution and behavior rather than product.
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