Yagini's Profound AI Rep
Yagini turns dense information into sharp, decision-ready outputs across investment and consumer research.
Yagini Airan
Edges
Running Primary Research End to End
Yagini owns research from the initial brief through to the final output, without handing off the thinking at any stage. She designs the questions, generates the analysis, and decides what the findings actually mean. This pattern showed up at Honasa, where she designed a consumer survey for The Derma Co. with Kantar, owned the analysis of the raw data, and translated the findings into a restructured marketing strategy. It showed up again at Stride, where she built sector views on fintech and defense tech from open-ended briefs with no prescribed structure. What distinguishes her approach is that she starts with the question she is trying to answer, not the data she has available. The structure of the output follows from what the audience needs to understand, not from what is easiest to organize. The result is research that is usable, not just thorough.
Spotted in 3 Stories
Synthesizing Qualitative Depth into Sharp Outputs
Yagini takes large, unstructured bodies of information and produces outputs that are short, clear, and decision-ready. She does not organize data; she builds a narrative around what the data actually supports. At Stride, she turned knowledge from roughly 200 fintech company conversations into a three-to-four slide narrative that showed where the market was going and why Stride was positioned to benefit. At Honasa, she took raw consumer survey data and produced a point-by-point comparison of what the brand believed against what the data showed. Her calibration instinct is strong: she adjusts the depth and scaffolding of an output based on what the audience already knows. For a technical space like defense tech, she builds the sub-sector context first. For a familiar space like fintech, she skips the basics and goes straight to the market narrative. The outputs she produces are consistently sharp and well-structured, and they have been used in LP conversations and brand strategy decisions.
Spotted in 3 Stories
Forming Independent Sector Views
Yagini goes deep enough into a sector or technology to form her own view, rather than synthesizing what others have already concluded. She starts from the underlying mechanics and works outward. When evaluating a deep-tech London startup that did not fit any existing sector classification, she worked through the company's technology from first principles, going through videos, technical documentation, and the website until she understood what the product actually did. From that, she formed an independent view that simulation within defense tech was a significant and underappreciated opportunity. She also identified cross-sector applications, including digital twins and natural disaster risk modeling, that went beyond the original deal context. This pattern of going deep enough to see what is not yet obvious is consistent across her work at Stride and Honasa.
Spotted in 2 Stories