Onkar's Profound AI Rep
Onkar turns raw on-chain data into structured sector views and acts on them in early-stage deals.
Onkar Thakur
Edges
Building Sector Research from Raw Data
Onkar builds research from the ground up, starting with raw data sources rather than secondary summaries. He scrapes, filters, and structures data before forming a view. This pattern showed up at Hashed Emergent, where he owned the full data pipeline for the India Blockchain Landscape report, and at Asva Capital, where he ran primary due diligence on founder claims before taking them at face value. His process combines quantitative data pulls with direct conversations: he talks to founders, users, and officials to pressure-test what the numbers show. The result is research that holds up when challenged, because it is built on verified inputs rather than aggregated assumptions.
Spotted in 3 Stories
Forming Independent Crypto Market Views
Onkar forms his own market views by combining on-chain data, VC portfolio signals, and direct product use. He does not wait for consensus before shifting his thesis. He tracked the meme coin cycle on Pump.fun, identified the trust erosion from scam projects, and moved his focus to prediction markets and remittance before the broader market followed. He sourced Polymarket at an early valuation and referred it to his angel network ahead of the US election cycle. His process is deliberate: he reads investment reports from top VC firms, tracks recent fundraising for traction signals, and tests products himself to see what is actually gaining adoption. When the evidence changes, he changes his view. He shifted from meme coins to prediction markets and remittance based on behavioural signals he observed directly, not on published narratives.
Spotted in 3 Stories
Structuring Sector Narratives for Investors
Onkar takes raw data and structures it into sector narratives that investors can act on. He organizes findings into verticals, sub-verticals, and geographic maps rather than leaving them as data dumps. At Hashed Emergent, he structured the VC investment data for the India Blockchain Landscape report into a format that surfaced the narrative shift from meme coins to infrastructure and stablecoin payments. He also worked on the African landscape slides, where he brought contradicting data to a team discussion and helped shape the final framing of a contested sector theme. His outputs are designed to be used: by VCs looking for a read on the market, by teams making investment decisions, and by founders understanding where capital is flowing.
Spotted in 2 Stories