There’s a frustrating gap that anyone who has run a single market research study knows well. Form builders like SurveyMonkey are quick to set up, but they don’t weight your sample or test significance. Enterprise platforms like Qualtrics do all of that properly, but they’re built for annual contracts and multi-team programs, not a brand manager who needs one clean study done before a product launch. Most teams end up either trusting numbers they shouldn’t, or paying far more than the study justifies.
Wavefield Research, an AI survey platform founded in Ontario in 2026, is trying to close that gap. The concept is simple: upload a brief, let an AI agent program the full questionnaire, field it with your own respondent list or a shareable link, and get back weighted, significance-tested results the same day. No annual contract, no per-seat pricing, no sales call. You pay per project, starting at $99, and the analysis layer that usually costs a separate analyst is included by default.
It’s a sharp product premise, and judged against the platform’s own documentation, it largely holds up.
Key Features of Wavefield Research
AI Agent Survey Programming
The core feature is an AI agent that reads a plain-language brief or an uploaded Word document and builds the entire survey: question blocks, skip logic, quota cells, answer rotations, and even translations. You can refine the output by chatting with the agent or editing directly in the visual editor. Both interfaces edit the same underlying document, so nothing gets out of sync when you switch between them. What traditionally takes a specialist programmer days to turn around happens in minutes.
Built-In Weighting and Significance Testing
This is where Wavefield earns its “defensible numbers” tagline. Every report shows weighted percentages alongside unweighted base sizes, and significance testing on crosstabs is computed on Kish effective bases, not raw counts. Weighting always costs precision; the platform accounts for that honestly rather than inflating confidence. Margins of error are reported as the convention they are for quota samples, not implied as probability-sample guarantees.
Quality Controls Baked Into Fielding
Speeders, straightliners, duplicate submissions, and low-effort open-ended answers are flagged automatically during data collection. Crucially, they’re flagged for review, not silently deleted. Excluded rows stay in raw exports with a label, keeping the audit trail intact. Quotas fill and close themselves. Screener terminates run cleanly.
Analysis Exports Without the Add-On
When a study closes, you get a print-ready weighted topline, a banner book in Excel, the full dataset as SPSS or CSV, and crosstabs with significance letters. The agent also codes open-ended responses into themes. On comparable enterprise platforms, several of these outputs sit behind add-ons or analyst services. Here they’re included in the project price.
Marcus at 9pm, Trying to Save a Tuesday Morning Presentation
Consider a hypothetical example — call him Marcus. He runs brand strategy at a mid-size consumer goods company. At 9pm on a Sunday, he realized his Tuesday boardroom deck needed actual consumer data to support a proposed repositioning, not just anecdotal feedback from a few interviews. His usual research vendor had a two-week minimum turnaround. Qualtrics required a sales call just to get pricing.
He created a Wavefield account, typed out a brief describing the study objectives: brand awareness, purchase intent, and three concept reactions among the company’s opted-in consumer community. By 9:40pm, the AI agent had drafted a 20-question survey with a screener, a brand funnel block, a concept rotation block, and a demographics close. Quotas were set at 50/50 gender with age targets.
Marcus reviewed the draft, asked the agent to anchor “None of these” on the brand list and add a Spanish overlay. Both changes took under two minutes. He uploaded the company’s opted-in contact list and sent single-use email invitations that night.
By Monday afternoon, n=400 completes had come in. The weighted topline was ready immediately. He saved the weighted topline as a PDF and downloaded the Excel banner book, dropped the key significance-tested crosstabs into his deck, and walked into the Tuesday meeting with numbers he could actually defend when the CFO pushed back. He cited effective bases and margins of error. The repositioning got approved to move to phase two.
How Wavefield Takes a Brief to a Finished Study
Step 1: Brief In, Survey Out
Upload a Word doc or describe your study in the chat interface. The agent drafts every block, including terminates, quotas, and rotations. You refine via chat or the visual editor.
Step 2: Field with Your Own Respondents
Publish a shareable link, invite your own contacts with single-use email links, or add SMS delivery for audiences that don’t live in their inbox. Quotas and screeners manage themselves. Quality checks run automatically in the background.
Step 3: Results, Not Just Exports
Once fielding closes, the platform produces weighted toplines, significance-tested crosstabs, trend lines for tracker waves, and coded open ends. Download in SPSS, Excel, or CSV. No analyst required for the standard output.
Pricing
Wavefield charges per project with no subscription required. Building a survey is free; you pay only when you field. Project pricing runs from $99 to $299 depending on study complexity. There are no per-seat fees and no annual commitments. SMS invites are included on every plan, with allowances from 1,000 to 5,000 texts by tier.
Worth Trying If You Need One Study Done Properly
Wavefield Research isn’t trying to replace a full enterprise research stack. It’s for the brand team, the startup, the political campaign, or the consultant who needs one study done to a proper methodological standard without signing a contract. The AI programming alone saves days of back-and-forth with a specialist. The built-in analysis removes the most common excuse for skipping the hard parts of survey work. Try it at wavefieldresearch.com.
