You're about to send 5,000 cold emails. But you don't know if anyone cares.

Test your offer against AI-simulated audience panels before you spend a dollar on leads or outreach. 50 synthetic decision-makers read your email, share their honest reaction, and score it. Results in minutes — not weeks.

Test Your Offer Now See How It Works

No credit card required. First panel results in under 5 minutes.

Why most cold emails fail — and how to know before you send

The offer isn't bad. You just tested it on your wallet instead of a panel.

The old way

Write a cold email, buy 500 leads, send, wait 2 weeks for 3 replies
Rewrite, buy 500 more leads, send again, wait 2 more weeks
After $2K and a month you still don't know if it's the offer, the audience, or the copy
Each test burns real contacts who won't open your next email
By the time you've iterated, competitors already closed those prospects
Focus groups cost $5K-15K and take a month to run

With AI panels

Paste your cold email. AI builds a panel of 50 simulated decision-makers
Each panelist has a real job title, company size, industry, tech stack, and pain points
They read your email and share their honest stream-of-consciousness reaction
Mean response score + full distribution in under 10 minutes
Iterate on copy, messaging, and targeting — zero leads burned
Launch only when the panel says 'this works'

Here's exactly how it works — four steps from offer to verdict

Paste your email. Get a verdict. Iterate until it's ready.

Four steps. No leads burned. No budget wasted.

Create Your Offer

Paste your cold email — subject line and body. That's the only input. The system treats this as the stimulus your panel reacts to.

Build Audience Panels

AI analyzes your offer and generates targeted audience segments — job titles, seniority levels, company sizes, tech stacks, and hiring signals. Each segment gets populated with real company data from Apollo.

Run the Panel

Each simulated decision-maker reads your email in character — their job, their company, their priorities. They share their honest reaction and score 1-5. Two samples per lead for reliability.

Read the Results

Mean response score, full 1-5 distribution, per-audience breakdowns. See which segments are cold and which are warm — before you spend a cent on outreach.

Sample panel results — what you'll actually see

Real output format. These numbers tell you exactly where your offer lands before you send.

3.72

Mean Response Score

(out of 5.0)

Score Distribution — 48 panelists

1 — Delete/spam

2 — Ignore

15%

3 — Skim, won't reply

27%

4 — Interested

35%

5 — Would reply

17%

High match 4.21

VP Sales at Mid-Market SaaS

51-200 employees · Series A-B · Sales-led

"This hits a real pain point for us. We've been looking at..."

Medium match 3.44

Director of Marketing at Enterprise

1,000+ employees · Series C+ · Hybrid GTM

"Interesting but we already have something in place. Maybe if..."

Low match 2.13

CTO at Early-Stage Startup

1-10 employees · Pre-seed · Product-led

"Not relevant to us right now. We're focused on shipping..."

Sample panelist response — what they're thinking when they read your email

Sarah Chen, Head of Growth

TechFlow Inc · 85 employees · Series A · React, HubSpot, Stripe

"Hmm, this subject line is specific enough that I'd open it. The body mentions a problem we actually have — our outbound reply rates have been dropping. But the ask is too aggressive for a first touch. If they'd offered a case study instead of jumping straight to a demo, I'd probably reply. Scoring this a 3.5 — interested but not enough to act."

Score: 3.5 / 5.0 Sample 1 of 2

50+

Panelists per run

Samples per lead

Scoring dimensions

< 10 min

Time to results

Test Your First Offer

Paste your email. Get a score. Iterate for free.

What makes these panels different from asking ChatGPT

Not a chatbot with an opinion. A research panel with data.

Every component is built to make the simulation as close to reality as possible.

AI Audience Building

The system analyzes your cold email and generates targeted audience segments using Apollo API filters — seniority, job title, company size, revenue range, technology stack, and hiring signals. Each segment splits into high-competition (obvious buyers your competitors also target) and low-competition (non-obvious audiences that respond well but are untapped). You test both before choosing where to spend your outreach budget.

Dual Scoring Methods

DTS (Direct Thought Scoring) generates stream-of-consciousness reasoning plus a 1-5 score — human-readable and easy to act on. SSR (Synthetic Survey Research) embeds free-text responses and compares them against multi-dimensional reference anchors using cosine similarity — six dimensions covering action, interest, probability, value, relevance, and trust. Use DTS for quick iterations. Use SSR for research-grade precision. Use both for cross-validation.

Lead Enrichment from Real Websites

Each lead's company homepage is scraped and analyzed — extracting company description, value proposition, target customer, pain points, tech stack, go-to-market motion, and communication tone. When a simulated panelist reads your email, they're not a blank slate. They have context about their own company's priorities, challenges, and stage — just like a real person deciding whether to reply.

Per-Audience Segment Breakdowns

The panel doesn't just give you one number. It breaks results down by audience segment — so you see that VP Sales at mid-market SaaS scores 4.2 while CTOs at enterprise companies score 2.1. That tells you exactly which segment to target and which to skip. You don't just learn whether your offer works — you learn who it works for.

CSV Lead Import

Already have a lead list? Import it via CSV. The panel runs against your actual prospects — not generic personas. If you have 200 leads from a trade show, test your offer against those specific people before you write the first email. Import includes name, job title, company, industry, seniority, and any firmographic data you have.

Run Your First Panel

Real audience data. Real scoring. Zero leads burned.

How does this compare to focus groups and survey tools?

Honest comparison: this vs. the alternatives.

Every method of testing offers has trade-offs. Here's where each one fits.

	AI Panels	Focus Groups	Survey Tools	Just Send It
Cost per test	Pennies LLM API calls only	$5K-15K Recruitment + facility + moderator	$150-500 $3-5 per real respondent	$500-2,000 Leads + sending infrastructure
Time to results	Under 10 minutes 50 panelists, scored and aggregated	2-4 weeks Recruitment + scheduling + analysis	3-7 days Wait for enough responses	1-2 weeks Send, wait, tally replies
Iteration speed	Unlimited Change copy, re-run, compare in minutes	1 per month Each round costs $5K+	Slow New respondent pool each time	2-3 per month Each test burns contacts
Audience targeting	Apollo-sourced segments Real titles, companies, tech stacks	Hand-recruited Small sample, often biased	Panel providers Generic, self-selected	Your lead list One-shot, contacts burned
Reasoning visible	Full stream of thought Read why each panelist scored the way they did	Transcripts available Expensive to analyze	Multiple choice only No reasoning	Reply content (if any) Most just ignore

AI panels don't replace real-world testing. They replace the first five iterations you'd otherwise do with real leads and real money. Test cheaply here, then deploy your winning version to the real world.

Zero risk. See for yourself.

No credit card required

Run your first panel and see real results before you're ever asked to pay. Judge the quality yourself.

Cancel anytime

No contracts, no annual lock-in. Export your panel data and audience segments. Your research leaves with you.

Results in under 5 minutes

Paste your email, run the panel, read the scores. Iterate as many times as you want. Each run costs pennies in API calls.

Try It Free

Try it free, cancel anytime.

Why I built this

I was writing cold emails and testing them the expensive way — buy 500 leads, write the email, send the campaign, wait two weeks, count the replies. Three replies out of 500. Was the offer bad? The audience wrong? The subject line? No idea. So I'd rewrite, buy another 500 leads, and try again.

After burning through $3,000 and six weeks of lead lists, I had a 2% reply rate and no idea which variable made the difference. The leads I burned on the first four drafts were gone forever — they'd already decided to ignore me.

I started wondering: what if I could test the email on simulated people first? Not "ask ChatGPT if this is good" — but actually build a panel of 50 decision-makers with real job titles, real company contexts, real pain points — and have each one read the email and tell me what they honestly think? If the panel scores it a 2.1, I know not to send. If it scores 4.3, I launch with confidence.

That's what this is. AI-simulated audience panels that score your cold email before you burn a single lead. Test the offer, test the audience, test the copy — iterate for pennies until you find what works. Then send the winning version to real people.

Common questions

Each panelist is built from real company data — scraped homepage, real job title, actual company size, detected tech stack, and industry context. They're not generic personas. They read your email as someone in their specific role and situation. The scoring isn't perfect — no simulation is — but it's accurate enough to separate a 2.0 offer from a 4.0 offer before you spend real money finding out.

ChatGPT gives you one opinion with no context about who the reader is. This system builds 50 different panelists with distinct firmographic profiles — different job titles, company sizes, industries, funding stages, and pain points. Each one reacts independently. You get a distribution, not an opinion. A mean score of 3.2 with high variance tells you something very different from a uniform 3.2. And you see which audience segments love it versus which ones don't care.

Name, job title, company name, company size, industry, funding stage, seniority level, tech stack, revenue range, location, hiring activity, time in role. For enriched leads, also: company description, value proposition, target customer, pain points, go-to-market motion, and communication tone. The more context, the more realistic the reaction.

Yes. Upload a CSV with name, job title, company, industry, seniority, and any firmographic data you have. The panel runs against your actual prospects. If you're about to email 2,000 leads from a conference, test your email against those exact profiles first.

Start with DTS (Direct Thought Scoring). It gives you readable reasoning — you can see exactly why each panelist scored the way they did. SSR (Synthetic Survey Research) uses embedding similarity across six dimensions for more granular scoring, but the output is less immediately actionable. Most users run DTS for fast iteration and add SSR when they want research-grade cross-validation.

The default is 10 leads per audience segment, with 2 samples per lead — so 20 data points per segment. Five segments gives you 100 total responses. That's enough to see clear patterns. More leads give more statistical confidence, but 10 per segment is the sweet spot between speed, cost, and signal quality.

The panel scores any offer that can be expressed as a subject line and body text. Cold email is the primary use case, but people also test LinkedIn messages, SMS sequences, ad copy, and even pricing page headlines. If you can paste it as text, the panel can score it.

Every untested email you send is a lead you can never email again.

The version that would have gotten a reply is one panel run away.

Test Your Offer Free

No credit card. No contacts burned. Results in minutes.