Swastik's Profound AI Rep
Swastik's view on research shows how he separates pattern from noise and builds views that are genuinely his own.
Swastik N.
Edges
Structuring Research from Ambiguous Briefs
Swastik builds structured research frameworks in situations where the brief is vague, the market is poorly mapped, or the available information is fragmented and conflicting. At Gain, he has done this repeatedly on private companies where public information is limited, inconsistent, or sourced from unreliable outlets. At Scholaride, he designed the research methodology from scratch for each client engagement, starting with secondary research to eliminate what was already known before designing questionnaires around the gaps only a primary source could fill. His process starts with the decision the research needs to support, breaks it into core hypotheses, and treats the initial framework as live rather than fixed. As new information comes in, the structure evolves. The result is research that is usable: logically sequenced, triangulated across sources, and structured so that someone unfamiliar with the subject can follow it and act on it.
Spotted in 2 Stories
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Pattern-Level Sector Thinking
Swastik does not analyze companies in isolation. He groups them, looks for what they have in common, and asks what the pattern reveals about where a sector is heading. He applied this to 314 Capital's portfolio, grouping companies by sector and identifying the investment thesis behind the fund rather than summarizing individual companies. He applied it to vertical AI, selecting companies across legal, healthcare, coding, and enterprise productivity to test whether workflow ownership or model quality was the real competitive moat. He applied it to quick commerce, tracking how VC scrutiny shifted from category momentum to unit economics as cash burn became the defining constraint. In each case, the view came from observing the same pattern repeatedly across different companies and contexts, then testing it against new examples rather than treating it as a conclusion. The output is a hypothesis that is genuinely his own, grounded in evidence, and useful for evaluating whether a specific company is riding a real trend or short-term noise.
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Designing Primary Research Inputs
Swastik designs the research methodology before gathering data, not after. At Scholaride, he built custom questionnaires for each client engagement, doing secondary research first to eliminate questions that could be answered from existing sources, then designing questions around the gaps only a founder or customer could fill. At Anand Rathi, he used structured client questionnaires to understand risk appetite, investment horizon, liquidity needs, and constraints before tailoring financial solutions. He also conducted expert interviews with equity mutual fund managers to understand stock selection processes. The discipline is consistent: define the decision the research needs to support, identify what secondary sources cannot answer, then design the primary research instrument around those specific gaps. This is an emerging pattern. The contexts are real but limited in number, and the primary research has been conducted in consulting and wealth management settings rather than formal investment research.
Spotted in 1 Story
Swastik N.
About Me
Swastik is a private markets researcher and early-career analyst with experience spanning investment research, consulting, and wealth management. He co-founded Scholaride at 19, scaling it to 30-plus members and 10-plus clients within 10 months.
He currently works as a Junior Analyst in the Private Equity Intelligence division at Gain, covering US, UK, and Canadian markets. His work involves building and maintaining comprehensive company profiles across business models, competitive positioning, financials, and ownership structures for top-tier investment management and PE/VC clients.
At Scholaride, he ran research and consulting engagements end-to-end: designing client questionnaires, conducting founder interviews, synthesizing findings into revenue model recommendations, and delivering outputs in pitch decks and Excel-based scenario models. One engagement produced a 15% revenue uptick for a T2/T3-focused digital services startup within a single quarter.
Earlier, at Anand Rathi, he worked with UHNW clients on portfolio strategy and asset allocation, conducting client interviews and surveys to tailor financial solutions.
Swastik N.
I rarely stop at understanding what happened. I want to know why it happened, whether it's part of a larger pattern, and whether that pattern will persist.”
Swastik N.
On forming a real view