Gaurav's Profound AI Rep
Gaurav structures research around decisions and connects macro signals to specific, testable market calls.
Gaurav Harlalka
Edges
Structuring Research Around Decisions
Gaurav does not start with a list of questions. He starts with the decision that needs to be made and works backward to identify what information would actually change the answer. This pattern showed up at Birla Carbon, where he built a three-branch decision tree before conducting a single interview, and at Gobuild, where he segmented his primary research across customer types to test whether the problem was structural or isolated. His method is to map the decision first, then identify who holds each piece of the answer, then sequence the research so that each conversation builds on the last. External data sources come in when internal ones cannot resolve the question. The result is research that is scoped to what matters, not exhaustive for its own sake.
Spotted in 3 Stories
Connecting Macro Trends to Market Calls
Gaurav reads macro signals and connects them to specific, actionable market positions. He does not stop at identifying a trend; he traces it through to a specific product, customer, or timing decision. At Grasim, he spotted the sustainability trend among Western brands, connected it to a specific production advantage in Indian viscous filament yarn, and identified Vietnam as the market where that advantage would matter most. The team validated the thesis in market. At Gobuild, he analyzed the Russia-Ukraine buildup alongside seasonal steel demand patterns in northeast India, identified a scenario where prices would rise under either outcome, and made a specific inventory call that generated 33% returns in four months. The pattern is the same: a macro observation, a specific mechanism connecting it to a market, and a testable call.
Spotted in 2 Stories
Building Analysis Decision-Makers Can Interrogate
Gaurav structures his outputs so that a decision-maker can either skim the conclusion or go deep into the reasoning. He does not present findings as a verdict; he presents the logic chain that produced them. At Birla Carbon, he walked the CEO through the decision tree, the stakeholders consulted, and the conditional nature of the recommendation, rather than presenting a single answer. At DSG, when his view on Faye Beauty diverged from the investment team's, he walked them through the specific people he had spoken to, their demographics, and the reasons behind their responses. His instinct is that senior decision-makers will not take a conclusion on trust. They want to see how it was reached so they can correct the reasoning if it is wrong, or update their own view if it is right. This makes his analysis more durable: it can be stress-tested, not just accepted or rejected.
Spotted in 3 Stories
Launching Categories from Zero
Gaurav has built new business categories from scratch twice, in contexts with no existing playbook, no supplier base, and no prior sales. At Gobuild, he started with primary research, built a thesis, raised capital, onboarded customers, and scaled to ₹25Cr ARR. At Birla Pivot, he learned a new product category, educated the team, onboarded 50+ suppliers, and drove the category to ₹13Cr per month in sales. In both cases, he owned the full arc: the research, the supplier development, the commercial execution, and the iteration based on what the market told him. The pattern is that he does not wait for a structure to exist before operating. He builds the structure as he goes.
Spotted in 2 Stories