Why we're building an AI market research employee, not another survey tool
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.
A single market research study touches six to ten disconnected tools: Qualtrics for surveys, SPSS for stats, NVivo for qual coding, a panel provider for sample, Zoom for IDIs, PowerPoint for the report, SharePoint for the archive. It pulls in four to six specialists: a research designer, a quant analyst, a qualitative analyst, a data scientist, a moderator, a presentation designer. It burns three to twelve weeks and $30k–$250k per project.
And at the end of all that, the insight is locked inside a 60-slide PDF nobody opens twice.
The insight
Every one of those specialists is executing a well-defined craft: writing a questionnaire, running a cross-tab, coding open-ends, spotting a theme in a transcript, building a persona, writing an exec summary, laying out a slide.
Large language models and multimodal AI are now good enough to do each of those crafts at the level of a competent mid-career analyst — if they are given the right scaffolding, the right tools, and a memory that persists across studies.
A market research team is not an inherently human thing. It's a set of skills wired together by a workflow. That workflow can be run by one AI employee with the right tools.
What weev is
weev is an AI market research employee. You talk to her like you'd talk to a senior analyst — in plain English, over chat or voice. She owns the whole study lifecycle: drafts the questionnaire, programmes the survey, conducts the interviews (over Zoom, in her own voice, in real time), cleans and codes the data, runs quant and qual analysis, finds the story, writes the deck, and remembers everything for next time.
One interface. One employee. All the skills of a full research department.
Why the framing matters
weev is not a SaaS tool. It is a hire. That framing changes everything:
- Pricing is per-employee, not per-seat or per-project.
- Onboarding is "here's our brand book and past studies," not a ten-tab config screen.
- The interface is a conversation, not a dashboard.
- The output is a deck a human would write, not a CSV a human has to interpret.
Humans stay in the loop where taste and judgement matter: setting objectives, steering the narrative, approving the final story. weev handles everything else.