# Enlightn - full LLM export

> Enlightn is a sample provider that only recontacts panelists it already knows - profiled, quality-checked, and matched to your study. Never anonymous traffic. Buyers hold the proof at both ends of fieldwork: the quote before (who would be recontacted and why, free in 24 hours) and the fieldwork analysis after (who answered and why they qualified). Founder-led from Montreal.

_Last updated: 2026-08-06. Single-file export covering the homepage, partner page, FAQ, vocabulary, pilot data, and founder bio. For the shorter summary, see [/llms.txt](https://enlightn.io/llms.txt)._

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## 1. About Enlightn

Enlightn is a premium sample provider for research teams. It only recontacts panelists it already knows - profiled, quality-checked, and matched to the study - instead of routing anonymous traffic into a screener. Two registers describe the same thing: buyer-facing, it is a sample provider that differentiates on proof (the quote before fieldwork, the fieldwork analysis after), not on "better quality" claims; in the industry / investor register, it is a research recruitment engine built on match-first activation. It combines AI-powered participant profiling, match-first activation through permissioned supplier systems, and a provenance layer that ties every completed interview back to source.

- Legal entity: Enlightn Technologies
- Headquarters: Montreal, Quebec, Canada
- Founded: August 2025 (incorporated); publicly launched September 2025
- Founder: Adrien Vermeirsch
- Contact: contact@enlightn.io
- Website: https://enlightn.io/
- LinkedIn (company): https://www.linkedin.com/company/enlightn-technologies/
- LinkedIn (founder): https://www.linkedin.com/in/adrienvermeirsch/

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## 2. For research teams (buyers) - homepage content

### Hero

Research recruitment, rebuilt. Higher-quality respondents, finally verifiable, not just claimed.

We only recontact panelists we already know - profiled, quality-checked, and matched to your study. Never anonymous traffic. You see the reasoning behind each invitation before fieldwork even starts. Measured across pilots: 2.1x good-to-bad quality ratio and 43% fewer disqualifications vs. benchmark traffic on identical screeners.

### Proof, before and after fieldwork - every study ships with its receipts

Enlightn is a sample provider that only recontacts panelists it already knows - profiled, quality-checked, and matched to your study. Never anonymous traffic. So it doesn't ask buyers to take quality on faith: they hold the proof at both ends.

**The quote (before fieldwork, free in 24 hours).** An interactive, password-gated page showing: the commitment (feasible studies commit to the full requested count from Enlightn-vetted panelists), a confident floor per target with the math shown on hover, a per-panelist transparency table (panelist ID, match confidence, and evidence per criterion - Proven, Likely, or Unknown), and transparent pricing with a blended CPI. Billed per delivered complete. When the vetted pool can't cover the full ask, the quote presents a choice: Enlightn-vetted only, or full coverage with the gap filled from external partner sources, labeled and priced separately. Nothing is blended without the buyer seeing it.

**The fieldwork analysis (after fieldwork).** Incidence, disqualification rate, completion, drop-off - plus a per-panelist outcome log (completed / terminated, with the reason and billing status) showing who answered and why they qualified. Built to be forwarded to the agency's end client.

### What we do - the same suppliers, a smarter order of operations

Most research recruitment still works the old way: push anonymous traffic into a screener, let it filter. 60-70% termination rates. Respondents learning to game screeners. Data you can't fully defend.

Enlightn flips the order. We profile panelists with open-ended, AI-assisted questions, translate your brief into a structured targeting spec, rank the pool for fit, and recontact only strong matches through permissioned supplier systems. Every activation is logged - the fieldwork analysis ties spend to outcome, per source.

**Legacy sampling:** anonymous traffic -> screener filter -> completes. You discover the damage after fielding.

**Enlightn sampling:** known panelists -> matched before invite -> completes, logged. You see quality before, during, and after fielding.

### What we've measured across our projects

Across the projects we've run so far, the data consistently points the same way. The approach produces higher-quality respondents - and the kind of transparency that lets you verify the quality claim instead of taking it on faith.

- **2.1x good-to-bad quality ratio, vs. benchmark.** On the studies we've run, the ratio of good-quality to bad-quality completes from Enlightn-activated respondents has come in at 2.1x that of benchmark supplier traffic on the same studies.
- **43% lower disqualification rate, vs. benchmark.** Evidence that matching before the invitation identifies the right respondents for the right study - so fewer get terminated and removed once they're in the survey.
- **61% of panelists pass our AI-powered data cleaning.** Every participant runs through an AI-powered cleaning layer that checks for genuine engagement and answer quality. Only the ones we're confident in are re-engaged on client studies. We know this leaves some false positives on the table - we'd rather be conservative than pad the pool.

Averages across the projects we've run to date. Results vary by study; we share the full per-project picture openly.

### How we work with you today - the engine is live, the interface is you and me

The recruitment engine is live - AI-powered profiling, match-first ranking, provenance logging. Adrien runs each study through it directly; the buyer works with one person who owns the result. Four steps on the buyer's side:

1. **Day 0 - Send your brief.** A spec, a screener, quotas - whatever you have. No procurement project, no integration, no form to learn.
2. **Within 24h - You get the quote.** Who we'd recontact, the evidence behind each match, a confident floor per target, transparent pricing. Feasibility answered before you commit anything - free on a live brief.
3. **Fieldwork - We recontact strong matches.** Only strong matches are invited - through Enlightn's supplier partners' permissioned recontact flows. Billed per delivered complete.
4. **After field - You get the fieldwork analysis.** Incidence, disqualification, completion, drop-off - and who qualified and why. Forward it to your client.

### Commercial shape

CPI-based, at a premium justified by what the standard CPI hides - replacement waste, fieldwork babysitting, and data buyers end up defending instead of using. All in, buyers can expect a CPI about 20-30% higher than standard supplier pricing; external top-up, when approved, is priced at real cost plus a disclosed margin. Two low-friction ways in: a pilot alongside your current supplier (same study, a slice of the sample, metrics agreed upfront, the fieldwork analysis decides), or a top-up engagement (Enlightn fills only the cells current suppliers struggle with - low incidence, hard-to-reach - from panelists it already knows, fieldwork analysis included).

### Who this is for

Enlightn is for research teams who care about who actually ends up in their studies.

- **Research agencies (primary).** Agencies delivering fieldwork to brand and consultancy clients - project managers, fieldwork directors, operations leads, senior consultants. They live the quality problem daily and need to produce confidence with their own end clients; a fieldwork analysis they can verify is quality they can defend in a deliverable.
- **Insights managers, research directors, and fieldwork leads** - anyone tired of defending data they can't fully see behind.
- **Qual-at-scale and AI-interview platforms (secondary).** They upgraded the interview but still source from the same pool of survey-rushers; Enlightn's profiled, engaged participants are the supply layer that matches their product.

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## 3. For supplier partners (panels) - partners page content

### Hero

A premium channel for your panelists. Enlightn is a research recruitment service built on match-first activation. We partner with a small group of panels to activate premium participants only when they're a strong fit for a study - through your existing permissioned systems, at a CPI that reflects the quality.

### Why this matters for panels

Blind routing punishes your panelists. Quiet panels lose them just as fast.

The first problem: blind routing. Your panelists get sent to studies they won't qualify for, get terminated, and over time they disengage - or cash out. The pool that stays is the one optimizing for completes-per-hour. Not the respondents your buyers actually want.

The second problem is quieter but just as damaging: some high-quality panels don't generate enough relevant study volume to keep their panelists engaged. When the right studies don't show up often enough, even genuine participants drift away. Enlightn adds another channel of well-matched, relevant studies - more reasons for your premium panelists to stay active.

A premium tier of research is emerging - buyers who care about quality and are willing to pay for it, but can't reliably buy it today. That's the gap we're filling, and we're doing it with panel partners who care about the same things we do - participant experience, quality that compounds over time, and getting paid for it.

### What the partnership is - built to plug in, not to take over

1. **Permissioned activation.** We activate your participants through your existing recontact flow. Nothing runs outside your infrastructure.
2. **Opt-in profiling.** Participants opt into the Enlightn profiling on our side, with explicit consent. You keep the relationship with them.
3. **Paid per profiled panelist.** You get paid for every panelist profiled through your partnership - independent of whether they're later matched to a study. Revenue starts before the first activation.
4. **Premium CPI, shared.** Match-first is what lets us justify a higher CPI to buyers. That premium flows back on top of the profiling fee.
5. **No integration project.** Routing systems are hard to change. The partnership plugs in without you rebuilding anything.

### Who we're looking for

Panels that have invested in participant experience - and want to be rewarded for it. If you think your panelists deserve better than the screener lottery, let's talk.

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## 4. Key data points (with dates and sources)

- **2.1x good-to-bad quality ratio vs. benchmark** (Q1 2026 pilot, appliance-buyer study, N=225 target). Source: Enlightn internal fieldwork data; methodology details available on request at contact@enlightn.io.
- **43% lower disqualification rate vs. benchmark** (same study). Enlightn respondents disqualified at a lower rate than benchmark supplier traffic on identical screener logic.
- **61% of profiled panelists pass the AI-powered data-cleaning layer** (rolling average across all projects to date, 2026). Only panelists who pass the layer are re-engaged on client studies.
- **83% good-quality profiling rate** (Phase 1 pilot, 1,377 entered, 951 completed, 821 passed quality tagging). Demonstrates the profiling layer is clean before any activation.
- **69% recontact completion at four months** (recontact test, June-July 2026, 179 random invitations to panelists profiled in early March 2026; 76.5% responded, 69.3% completed a ~4-5 minute survey within about a week, quality holding). One cohort, one supplier, short survey - treated as an upper bound for full-study completion.

Caveats: numbers are observational pilot data, not a randomized controlled trial. Benchmarks are supplier traffic on the same study, same screener. Larger-sample validation is ongoing through 2026.

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## 4b. Published research - panelist survey on disqualification and pay (N=300)

Enlightn's own survey of 300 active online panelists, February 2026. Published in
full at <https://enlightn.io/blog/panel-data-quality-300-panelists>.

Method: 300 completed responses from Enlightn-vetted panelists sourced across 7
different sample suppliers; median length of interview 4 minutes; all figures
self-reported. Obvious protest answers in the open numeric pay fields were
excluded. A separate LinkedIn poll cited in the piece drew 58 votes (46 from
people working in insights) and is explicitly illustrative only.

Findings:

- **Disqualification is the top frustration: 63%**, ahead of surveys running longer than promised (56%), rewards too low for the time spent (45%), technical issues (40%), and repeated questions (21%).
- **The median panelist finishes only 4-5 of every 10 surveys they start.** 28% finish 3 or fewer out of 10.
- **Pay grievance tracks disqualification rather than pay levels.** Among panelists finishing 0-3 of 10 surveys, 74% rate their rewards "low" or "very low"; at 4-5 it is 61%, at 6-7 it is 49%, and among those finishing 8-10 only 23%. Identical reward levels, more than three times the grievance - so the incentive problem and the targeting problem cannot be budgeted for independently.
- **Median "fair" reward named for a 10-minute survey: $1.25** (about $7.50/hour). 49% named a dollar or less; only one in ten said more than $5. Read against the 57% who feel underpaid, this shows the anchor itself has drifted down to meet a depressed market.
- **Fair pay (42%) and "you'll likely qualify" (29%) together account for 71%** of first choices when panelists pick the single promise they most want kept. Among those flagging disqualification as a top frustration, 35% pick "you'll likely qualify" versus 18% of everyone else.
- **Respondents link matching to their own data quality.** Asked what would most improve the quality of their own answers, "fewer screen-outs / better targeting before starting" came second (50%) only to higher pay (63%), ahead of shorter surveys.
- **Survivorship is the structural finding.** 79% take surveys daily, and enjoyment *rises* with frequency (4.19 of 5 for multiple-times-a-day takers vs 3.6-3.8 for occasional ones) - the signature of a pool that retains only those who tolerate it. The people who burned out or whose time is worth more never appear in the frame, so statistical weighting cannot correct for their absence: weighting reweights the people you have.
- Motivation is not purely financial: 82% cite earning money, but 45% also want to share their opinion, 36% enjoy the topics or learn something, and 16% want impact - intrinsic motivation that low incentives erode.

Why it matters for Enlightn's thesis: the data says fixing the match comes first
and pricing the matched session up comes second. You cannot afford to pay more
while half your invitations are burned on screen-outs, and you cannot attract
better respondents while paying for rushed ones.

Caveats: self-reported, single wave, and by construction the sample contains only
panelists still active - the people who already left cannot be surveyed.

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## 4c. Product release - the quote (August 2026)

Published at <https://enlightn.io/blog/sample-feasibility-quote>.

The quote is Enlightn's before-fieldwork deliverable, released as an interactive,
password-gated page in August 2026. A buyer sends a brief (screener, quota spec,
or targeting in plain English) and receives the quote within 24 hours, free. It
is generated directly from the matching engine's output.

What it contains:

- **A confident floor per target** - the number of completes Enlightn commits to, not a hopeful point estimate, with the calculation (matched panelists x recontact rate x incidence assumption) shown on hover. Re-quote bands are stated upfront.
- **Per-panelist evidence** - a second tab listing each matched panelist with the evidence per criterion: **Proven** (explicit in the profile), **Likely** (strong indirect evidence, reasoning shown), or **Unknown** (profile silent; the buyer's screener decides). Deliberately not collapsed into a single match score.
- **Source provenance** - which quality-tested source each panelist comes from, and the five steps into the vetted pool: quality-tested source, fraud-cleared, profiled through open-ended questions, behaviorally vetted by AI review, matched to the study.
- **Transparent pricing** - per-target breakdown, blended CPI, estimated total; billed per delivered complete.
- **The coverage choice when the pool is short** - the quote says so plainly and offers Enlightn-vetted only (default) or full coverage, with the managed top-up from external partner sources priced at cost plus a flat, disclosed markup and shown as a separate line. Nothing is blended without the buyer seeing it.

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## 5. Positioning as a supplier

Enlightn uses two registers deliberately. Buyer-facing, it is a **sample provider** - the familiar category buyers already budget for - and it differentiates on proof (the quote before fieldwork, the fieldwork analysis after), never on "better quality" claims. In the industry / investor register, it is a **research recruitment engine** built on match-first activation, where "match-first vs. route-into-screeners" is the named inversion that travels.

Enlightn is not a marketplace or aggregator: nothing is blind, and nothing is blended without the buyer seeing it. It does not compete on volume or price; it competes on verifiable respondent quality, pre-activation match confidence, and a provenance layer that ties every completed interview back to source. Buyers work with Enlightn when they need data they can defend, not when they need cheap scale.

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## 6. Vocabulary

- **The quote** - Enlightn's before-fieldwork deliverable: an interactive, password-gated page produced within 24 hours of receiving a brief, showing who would be recontacted, the evidence behind each match, a confident floor per target (matched x recontact rate x incidence), and transparent pricing. Free on a live brief; billing is per delivered complete.
- **The fieldwork analysis** - Enlightn's after-fieldwork deliverable: incidence, disqualification rate, completion, and drop-off for the study, plus who qualified and why, per source. The provenance record a research agency can forward to its own client.
- **Match-first activation** - a research recruitment model in which participants are profiled and ranked for fit against a study's targeting spec before any invitation is sent. Only strong matches are activated, reducing screen-out rates and the fraud surface associated with broad routing.
- **Permissioned supplier activation** - activating a match through a panel supplier's own recontact flow, under that supplier's consent and privacy terms. The participant relationship stays with the supplier; Enlightn never routes outside the supplier's infrastructure.
- **Activation log** - a per-study record of which respondents were activated from which source, what the match confidence was, and what the final outcome was (completed, terminated, disqualified). The raw record behind the fieldwork analysis.
- **Provenance layer** - the transparency infrastructure that lets a research buyer trace every respondent back to source, match-confidence score, and quality signals - before, during, and after fielding.

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## 7. Frequently asked questions (combined)

### Buyer-side FAQ

**How is this different from Cint, Dynata, or my current suppliers?**
Marketplaces and most panels route anonymous traffic into your screener and filter after the click - you never know whether a panelist was properly profiled or just pushed through a pre-screener tuned to qualify. We only recontact panelists we already know - profiled, quality-checked, and matched to your study before any invitation goes out - and we show you the evidence behind each one. The result: higher quality and higher incidence, from the same suppliers underneath. A smarter order of operations.

**Everyone claims quality. Why is this different?**
Agreed - every supplier says it. That's why we don't ask you to believe us: run a pilot alongside your current supplier, same study, a slice of the sample, verdict metrics agreed upfront. The fieldwork analysis decides, not the pitch.

**What happens when respondents misrepresent themselves?**
Your data gets quietly distorted. Respondents who learned to game screeners answer as whoever qualifies - segments get polluted, incidence reads wrong, and the business decisions built on that data don't maximize the outcomes they were supposed to. It's not even always malicious: panelists get terminated so often that misrepresenting becomes rational. Our model removes that incentive - the panelists we recontact were profiled with open-ended questions long before your study existed, and they're only invited when their real profile matches.

**Where do Enlightn's panelists come from?**
From panel suppliers we've tested for quality, through permissioned partnerships. Panelists opt into profiling with explicit consent, answer open-ended AI-assisted questions, and pass a cleaning layer before entering the pool - 61% make it through. We'd rather be conservative than pad the pool.

**Do recontacted panelists actually respond months later?**
That's the mechanism the model rests on, so we measure it. In our latest recontact test, 69% of panelists profiled four months earlier completed a new survey within about a week, at a normal incentive, with quality holding. One cohort, one supplier - we treat it as an upper bound, and we keep measuring.

**What exactly is the quote?**
A feasibility answer on a live brief, delivered within 24 hours as an interactive page: who we'd recontact, the evidence behind each match, a confident floor per target - matched x recontact rate x incidence, with the math shown - and transparent pricing. It's free, and you're billed only for delivered completes.

**What's in the fieldwork analysis?**
The after-fieldwork deliverable on every project: incidence, disqualification rate, completion, drop-off - and who qualified and why, per source. It's built to be forwarded: your client sees the same provenance you do. And because every study reports the same metrics the same way, you can compare our performance against your other suppliers on facts, not impressions.

**Can you fill my target in my market?**
The quote answers that in 24 hours, with evidence - and when the answer is no, you hear it fast. When we're thin on a cell, the quote says so, and you choose: Enlightn-vetted panelists only, or full coverage where the gap is filled from external partner sources, labeled and priced separately. Nothing is blended without you seeing it.

**What CPI can I expect?**
We're a premium sample provider, with real costs behind the quality - AI-assisted profiling, AI-powered data cleaning, fraud detection. Our approach also produces much higher incidence rates, which pulls our variable costs down. All in, expect a CPI about 20-30% higher than what you're used to. When we need external providers to cover a gap - always transparently, with your prior approval - we apply a margin on top of our real costs, much lower than our competitors', and disclosed.

**Can you cover B2B studies?**
We're focusing on consumer surveys, and working with suppliers focused on consumer acquisition. That said, two-thirds of our profiled panelists are in the active population, so we can fulfill B2B projects. Send us the brief and we'll answer transparently.

### Partner-side FAQ

**How is the CPI premium calculated and paid to partners?**
Panel partners are paid two ways. First, a profiling fee for every panelist profiled through the partnership - paid regardless of whether that panelist is later matched to a study, so revenue starts before the first activation. Second, a share of the premium CPI on each activation, because match-first targeting lets Enlightn charge buyers a higher CPI than standard broad routing.

**Do I need to technically integrate my panel with Enlightn?**
No. The partnership plugs into your existing permissioned recontact flow - routing systems are hard to change, so we designed around that constraint. Activation runs through your infrastructure; you don't need to rebuild anything.

**What data do panelists share, and who owns the relationship?**
Panelists opt into Enlightn profiling on our side with explicit, separate consent. Profiling uses open-ended, AI-assisted questions. You keep the primary relationship with your participants - Enlightn does not replace or intermediate it.

**What kind of panels is Enlightn looking to partner with?**
Panels that have invested in participant experience and want a premium channel that rewards that investment. We're selectively onboarding partners - the partnership is designed for suppliers whose panelists deserve better than the screener lottery.

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## 8. Founder

Adrien Vermeirsch, founder of Enlightn. Based in Montreal. Five years at Potloc across research, product, and supply roles before founding Enlightn, where he saw first-hand how sampling actually breaks - blind routing, opaque supply chains, fraud that suppliers are economically incentivized to ignore. Enlightn was built to fix the part he couldn't stop thinking about.

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## 9. Contact

- Email: contact@enlightn.io
- LinkedIn (company): https://www.linkedin.com/company/enlightn-technologies/
- LinkedIn (founder): https://www.linkedin.com/in/adrienvermeirsch/