AI market researcher · in private beta
weev is an AI market researcher. Brief her like an analyst — a question and an audience — and she designs the questionnaire, schedules and conducts the interviews in her own voice, runs the quant and qual analysis, and delivers a client-ready deck in your brand. Days, not weeks.
How she thinks
A stakeholder drops a question on your desk. You paste it to weev. What happens in the next 60 seconds is the point of this company.
Monday · 09:14
Marketing wants to know how Bangalore is responding to your healthy-food range at AIB Mall. You paste the question to weev in a sentence.
Brief · AIB Mall
“We need to understand how urban Bangaloreans are reacting to healthy food options. Budget for n=12 IDIs and a brand perception module.”
09:14 · 8 seconds later
weev searches your team’s full archive by meaning, not keyword. Three prior studies jump out — same category, same geo, same brand codes.
3 relevant past studies
Jun 2025 · Phoenix Mall · Healthy QSR Perception
94%Nov 2024 · Orion · F&B Intent Tracker (Blr)
88%Mar 2025 · Quaker · Better-for-you Messaging
71%09:15 · plan ready
weev drafts the questionnaire, recommends the approach, and cites exactly what to build on from prior work. You approve, redirect, or fork — all in the same conversation.
Proposed plan · v1
awaiting approvalCapabilities
Six jobs a research team does. weev does all of them — starting with the one no human can do at scale.
Every study your team has ever run is searchable by meaning, not keyword. When a new question lands, weev pulls the studies that matter and proposes what to build on.
New brief · AIB Mall · healthy food · Bangalore
Jun 2025 · Phoenix Mall · Healthy QSR Perception
94% matchNov 2024 · Orion · F&B Intent Tracker (Bangalore)
88% matchMar 2025 · Quaker · Better-for-you Messaging Test
71% matchShe proposes the method, the questionnaire, and the discussion guide — grounded in prior work for this brand and category. You approve, redirect, or fork.
weev joins Zoom in her own voice, probes when answers are vague, and captures and codes the transcript as she goes.
weev · 0:34
“When you said ‘it just felt off’ — walk me through what triggered that. Was it visual, speed, or the copy?”
Cross-tabs, significance, segmentation, key drivers — written in plain English. Every number cites its source.
NPS by segment
Themes, entities, sentiment, personas — from transcripts, voice, or video. Every quote cites its timestamp.
Onboarding friction
42%Notification overload
31%Mostly negative · 68%
A client-ready deck in your brand, with an exec summary you can walk into the room with. Ready to present.
How it works
Two modes, one researcher. Have the responses already? Analysis and deck in 15 minutes. Need to field it? She schedules, conducts, and reports on the interviews herself — days, not weeks.
Brief or data · in chat
A questionnaire and responses? A brief and a target audience? Paste it in chat. weev recalls every related study your team has ever run and proposes the fastest path to an answer.
You approve the plan · one click
Quant-only: she writes the analysis, codes the opens, and stages the deck. Full study: she schedules the interviews, conducts them in her own voice, and transcribes as she goes.
Quant · 15 min · Qual · days, not weeks
Quant with data in hand: a branded deck with analysis in 15 minutes. Qualitative end-to-end: scheduling, interviewing, coding, and report across days — not the usual weeks.
weev vs. a human team
A full research operation used to take eight roles. weev collapses the production work into a single conversation — so your team spends its time on judgement and the decision, not the busywork.
~60% of the research workflow today. The rest is on the roadmap — see the manifesto.
Who hires weev
weev isn’t a dashboard you train a researcher to use. She is the researcher — briefed, onboarded, and running your first study in the same week.
Stakeholders ask questions faster than an outsourced tracker can answer. weev runs primary research at the speed of the question — so “we outsourced it, it’ll be back in six weeks” stops being your answer.
From quarterly tracker to ambient insight.
Need to validate a decision but don’t want to hire an agency for one question? Brief weev, get a real study back, make the call — in the same week.
Validate the call before you commit the budget.
You win on taste and judgement, not throughput. weev gives a small shop the output velocity of a large one — without changing how you sell.
Recall → design → field → deck loop in a week.
Case study
To show what weev actually produces, we ran a complete study on the on-demand home-help market in Dubai: questionnaire design, 20 in-depth interviews, quantitative and qualitative analysis, and a client-ready deck. This is the real output.
65% named “strangers in the home” as the primary barrier to adoption; fewer than 20% named price.
Ramadan, Eid, and post-party cleanups are the dominant unmet-demand windows.
70% would book by app, 0% by phone — and 71% won’t book without Emirates ID verification on the worker’s profile.
The market is real and the demand is there, but trust has to be built into the product before it asks for a booking.
A study we ran to demonstrate weev
Trust
Research lives and dies on methodology and provenance. weev is built so the chain of evidence never breaks.
Every answer cites the transcript, the row, or the past study it came from. No hallucinated statistics. No confident guesses dressed up as insight.
weev pauses at every irreversible step — scheduling interviews, sending a deck, anything that leaves your hands — and waits for your call.
Every deck, every doc, every slide is rendered in your brand's design system. Your stakeholders see your brand, not a vendor's. Always.
Studies stay yours. Respondent data stays yours. Nothing trains a foundation model. Ever.
Where she’s going
weev’s vision is a fully autonomous market research engine — one that decides what research to run, designs the study, runs it, analyses it, and delivers the answer. We’re building the foundation right now, one workflow at a time.
Tier 1 · Next quarter
Questionnaire designer, online survey hosting, panel integrations, fraud layer, key driver analysis, recommendations layer.
Tier 2 · Next six months
Conjoint, MaxDiff, NPS templates, brand tracker, focus group moderator, live dashboards, multi-user collaboration.
Tier 3 · The moat
The bets that make us un-clonable. Cross-study meta-insights, recommendation-to-experiment loops, workshop facilitator mode, client memory that compounds.
From the blog
Market research is slow because it's fragmented. Ten tools, six specialists, six weeks. Every one of those specialists is doing a craft AI is now genuinely good at. So we stopped building software and started hiring.
An honest capability inventory. What weev can already do end-to-end, what's a few weeks away, and what's deliberately not on the roadmap.
A real Zoom transcript from one of weev's IDIs. No editing, no scripting. Probing rules, pacing, and what we got right (and wrong) on the first dozen interviews.
Talk to weev
We’re onboarding our first teams now. Fifteen-minute call, no slides, no pitch deck. Just a question and a live demo with weev.