Vipul's Profound AI Rep
Vipul's view on research integrity shows how he separates evidence from expectation.

Vipul Sahu
Edges
Vipul builds market sizing models in markets where reliable data is scarce, using a combination of primary research, alternative data sourcing, and iterative pressure testing to arrive at numbers that hold up. He demonstrated this in the Iraq retail banking study, where the first model failed against primary research assumptions and he rebuilt it from scratch using World Bank data, executive interviews, and deep secondary research. His approach runs both bottom-up and top-down models simultaneously, then triangulates against qualitative findings until the outputs converge. The discipline is in knowing when to discard a model rather than patch it.
Spotted in 2 Stories

Vipul designs and executes primary research from scratch, including questionnaire design, stakeholder sourcing, data collection, coding, and synthesis into structured findings. He has run this loop across retail banking in Iraq, packaged snacks across Indian cities, and consumer electronics markets, each time owning the full process from brief to deliverable. His synthesis approach involves coding qualitative data into themes, then interpreting findings through multiple lenses, including investor, analyst, and client perspectives, to surface what actually matters for the decision at hand.
Spotted in 2 Stories

Vipul forms independent views on sectors by tracking benchmarks, investment activity, supply chain dynamics, and regulatory developments, rather than synthesizing consensus. He has formed grounded views on the AI valuation landscape, the competitive threat from open-source Chinese models, and the structural constraints on India's semiconductor ambitions, each backed by specific data points he tracks regularly. His monitoring approach combines Google Alerts, Screener, and Crunchbase with benchmark platforms, and he focuses on underlying shifts in customer behavior, technology viability, and regulation rather than surface-level news.
Spotted in 2 Stories

Vipul builds research workflows that use AI to accelerate output without removing the verification step, treating AI as a parallel workstream rather than a replacement for judgment. He built a custom AI research agent using an open-source model, programmed to his specific workflow requirements, and uses it to run deep research prompts while he works on other tasks simultaneously. His approach is to cross-verify every AI output against multiple sources before incorporating it, maintaining the rigor of the research while compressing the time required.
Spotted in 2 Stories
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Vipul Sahu
About Me
Vipul Sahu is a research analyst with three years of experience running end-to-end market research across tech, semiconductors, banking, consumer, and defense sectors.
He currently works at 6Wresearch, where he owns the full research loop: scoping briefs, designing primary research, building market sizing models, and delivering structured findings to clients.
At 6Wresearch, he led a retail banking dynamics study for Standard Chartered in Iraq, a data-sparse market, rebuilding the market sizing model from scratch after it failed pressure testing against primary research findings.
At EZ, he ran parallel research workstreams for MBB consulting clients, managing short-turnaround requests alongside longer custom reports across consumer electronics and ICT markets.
He also conducted a solo category assessment of the packaged snack market across Tier 1 and Tier 2 cities in India, completing 60 retail interviews and shelf audits that shifted the client's recommendation from broad expansion to a channel-specific strategy.

Vipul Sahu
Research is a tool for decision-making. If the findings challenge what a stakeholder expected, that's the point.”
Vipul Sahu
On research integrity