Sarthi's Profound AI Rep
Sarthi builds grounded M&A research from open-ended briefs and owns the full cycle from screening to delivery.

Sarthi Goyal
Edges
Sarthi structures research and analysis when the brief is vague, the market is poorly mapped, or the criteria have not been defined. He starts with what the client actually needs to decide, then builds the framework around that. This pattern showed up clearly in the European MedTech mandate, where he received no screening criteria and reverse-engineered the acquirer's priorities from prior deal history. It also shaped how he approached the Novartis deal materials, where he had to build the value case for a premium transaction from first principles. His process runs from stakeholder intent to research structure to evidence, rather than from data to output. He pulls from company filings, management commentary, broker consensus, and third-party research, then synthesizes into a grounded view. The result is research that holds up when a banker asks where a number came from.
Spotted in 2 Stories
Sarthi runs the complete M&A research cycle: from initial target screening through comp universe construction, valuation analysis, and client-facing deliverable preparation. He owns each stage rather than contributing to one part of the process. At WNS, this meant building screening criteria using S&P Capital IQ, narrowing universes of 260-plus companies down to five or six high-potential targets, running DCF and trading comps, and preparing pitchbooks and company profiles that went directly into live mandates. He backs every call with documented evidence. When bankers ask where a number came from, he has the source. When they push back on a target choice, he has the rationale. Across more than 50 research deliverables, this pattern has been consistent: he owns the work end to end and iterates until it lands.
Spotted in 3 Stories
Sarthi builds working sector knowledge quickly when moved into unfamiliar territory. When he transitioned from TMT to healthcare at WNS, he had no prior knowledge of drug development phases, NDA approvals, or how clinical trial outcomes move share prices. He ran a self-directed learning track alongside live work: reading sector primers, studying company filings from major healthcare players, reviewing prior team deliverables, and staying close to top performers. Within a month, he was operating independently and leading a small analyst team. His approach to sector ramp is structured: he identifies the technical vocabulary first, then maps how sector-specific events drive valuation, then builds his own view on individual companies. This pattern suggests he can cover new sectors without a long onboarding runway.
Spotted in 1 Story