Keshav's Profound AI Rep
Keshav's view on financial modeling shows how he separates a defensible model from a well-formatted spreadsheet.

Keshav Notani
Edges
Keshav builds financial models from scratch across two distinct contexts: early-stage startups and publicly listed equities. In both, the output is the same, a model grounded in sourced assumptions rather than founder optimism or analyst convention. At Egniol, he built over fifty models for pre-seed and early-stage startups, covering revenue, cost structure, burn rate, runway, and valuation. At his current role, he has built quarterly models for listed companies including Coca-Cola and GoDaddy, running DCF and relative valuation to issue independent ratings. His process starts with industry research before any founder or filing interaction. He runs revenue projections first, then works backward through the cost structure, using sourced benchmarks to pressure-test every major assumption. The distinguishing pattern is his willingness to show a founder or manager where their assumptions break down, using the model itself as the evidence rather than assertion.
Spotted in 3 Stories
E
Keshav approaches equity research through a structured reading of primary sources: 10-Ks, 10-Qs, MD&A sections, and risk disclosures. He reads across multiple years to track whether management's stated plans match their actual execution. His peer selection process is ratio-driven, using leverage and cash flow ratios to identify genuinely comparable companies rather than defaulting to obvious proxies. On Coca-Cola, this process surfaced a structural difference in bottling ownership that separated Coca-Cola's competitive position from Pepsi's in a way that headline comparisons miss. He focuses on three to four sections of each filing rather than reading comprehensively, prioritizing the financial statements, MD&A, and risk disclosures as the highest-signal sections. The output of this process is a research view grounded in what management has said and done, not just what the current quarter shows.
Spotted in 2 Stories
E
Keshav's work with early-stage founders consistently involved a specific challenge: founders who were optimistic about growth rates, cost structures, or market size in ways that the industry data did not support. His approach was to build the model first, then use it to show where the assumptions broke down. Rather than challenging founders directly, he let the numbers surface the gap, then walked through the sourced benchmarks that grounded his alternative view. This process surfaced a meaningful insight on the edtech robotics startup: the company's capital structure was closer to a hardware business than an edtech business, which changed the funding trajectory and the market framing entirely. The pattern across Egniol's startup portfolio was consistent: build the model, surface the gap, ground the conversation in data.
Spotted in 2 Stories


Keshav Notani
About Me
Keshav Notani is a financial analyst and investment researcher with experience spanning startup investment banking, strategy consulting, and equity research. He works across financial modeling, valuation, and business analysis, with exposure to both early-stage startups and publicly listed companies.
He is currently an equity research analyst, covering listed companies with a focus on fundamental analysis and primary research, building quarterly financial models and issuing buy, sell, or hold ratings grounded in DCF and relative valuation.
At Egniol, he built over 50 financial models for early-stage startups across edtech, fintech, and other sectors, supporting fundraising rounds and helping founders stress-test their assumptions against industry benchmarks.
At Jagdish Hirani, he led SOP development and ERP implementation for clients in banking and retail, diagnosing operational friction and designing streamlined processes for loan approval and account opening workflows.

Keshav Notani
A financial model that can't be defended assumption by assumption isn't a model. It's a spreadsheet.”
Keshav Notani
On financial modeling rigor