Every Knit project begins with a scoping flow that captures your objectives, audience, and the business context behind the ask. From that conversation — with an AI agent, your dedicated researcher, or both — Knit generates a Research Brief that makes every output relevant to your actual business question, not just the survey topic.
Most AI tools start with a blank prompt. Knit starts with context. You can kick off a project directly in Knit — answering a set of researcher-quality questions at your own pace directly in the platform, or work with your dedicated Knit researcher on a scoping call. Either way, what comes out is the same: a high-quality Research Brief that drives every output downstream.
Knit gives you two ways to scope a project. You can scope a project directly in Knit — using an AI-guided flow that asks the same questions a senior researcher would: your objectives, target audience, hypotheses, and what a successful outcome looks like. Or you can run a live scoping call with your dedicated Knit researcher, acting as a strategic thought partner. Either path produces a Research Brief that drives everything downstream. The choice is yours based on what the project needs.
From your scoping flow, Knit’s AI generates a Research Brief — a structured document capturing your audience definition, research objectives, hypotheses, and deliverable expectations. You’re able to collaborate with your dedicated human researcher via comments, a scoping call or with Knit’s AI to get it finalized before generating your questionnaire.
You can also share past research, brand guidelines, or examples of reports you love into your Research Context Library. Knit’s will factor those in so every study reflects how you uniquely run research. This context feeds into every output downstream. Your questionnaire is built on it. Your analysis plan references it. Your report is shaped by it. Every project you run on Knit gets smarter because of it.
Knit retains your preferences, past methodologies, and research history across projects. Every study builds on what came before — so your AI outputs reflect that institutional knowledge rather than treating every project like the first one.
Robust scoping helps Knit understand why a question matters to your business, what your stakeholders need to see in the output, or how your company defines success for this particular study. That’s what Knit’s scoping flow captures — and it’s why Knit’s outputs feel tailored, not templated. When your researcher and the AI are working from the same context, what comes back is a high-quality narrative you can share confidently.
Learn how NASCAR gathered, cut, and analyzed fan and non-fan input at scale to guide its in-season tournament launch strategy with the help of Knit.
Dig into how Knit is applying Researcher-Driven AI across every step of the research process.
Start with context. Use the scoping flow in the platform or work with your dedicated researcher — either way, you get a Research Brief that grounds every output in your actual business question.
Brief to questionnaire in minutes — AI-drafted, grounded in your research context and past examples
Bring your own audience or tap 65M+ vetted respondents. Knit handles fielding end-to-end.
Quant and qual analyzed together, automatically — guided by your Analysis Plan, cited and sourced.
A fully structured, branded memo and report with high-quality insights. Export to PowerPoint or Google Slides in one click.
Book a 30-minute demo and we’ll walk you through a real study — from scoping to final report — so you can see exactly how Knit works before you commit to anything.
