Swetha
Prabhakar
Building the thinking layer between raw data and real decisions — so people don’t just look at dashboards, they understand what they mean.
A structured intelligence layer that maps datasets into concepts, detects signal, and generates traceable narratives — the missing layer between spreadsheets and strategy.
Structured thinking, narrative systems, and the space between data and decisions
I enjoy solving problems that blend creative intuition with analytical depth. Today, I’m building a new kind of product — a thinking layer for data — that helps anyone explore, interpret, and act on information like an expert analyst. It’s not a dashboard, but a traceable, structured intelligence system that lives between raw data and real decisions.
It’s the missing layer between spreadsheets and strategy: a reasoning engine that transforms fragmented analysis into focused, interpretable insight. By rethinking how we structure exploration, guide attention, and reveal what matters, it helps people move from metrics to meaning — almost like magic. Over time, it will power everything from investment memos to strategic playbooks, offering a canvas for structured thinking as flexible as Notion, but with analyst-grade depth.
Before this, I spent more than a decade building consumer products at scale. At Snap, I led work across identity and creator monetization — including Public Stories and Profiles, Gifting/Tipping, Story Replies, and real-time payouts via Crystals. These were deeply cross-functional efforts developed with engineering, design, research, trust & safety, support, and more.
Earlier in my career, I founded and ran Fanvana (acquired) and worked as a data scientist at Facebook on Pages monetization — focusing on creator incentives, content performance, and ecosystem health.
I am also a PhD candidate in mathematics at Princeton, where my research centers on network structures, cluster dynamics, and the geometry of influence. My dissertation — informally known as Adler’s Algorithm — explores how tightly connected systems behave under stress, drawing inspiration from the game-theoretic insights of John Forbes Nash. While separate from Sway Interactive, this research shapes how I think about systems, incentives, and how information flows.