01
1Growth leadB2B SaaS
2Power userHigh intent
3New customerPrice sensitive
Define the audience
Upload customer context, describe your ICP, or start with a target segment.
See how your market reacts before you spend the budget.
Compare every campaign, pricing, positioning, and product decision against a defined model of your audience. Get the strongest candidate, the segment-level objections, and an explicit no-call — in hours, not weeks of research.
Simulation results
Variant ATop synthetic signalRange 68-79%
“Start your free trial”
74%
Variant BRange 45-58%
“See it in action”
51%
Variant CRange 30-44%
“Join 10k+ teams”
38%
Illustrative synthetic support report · validate in live traffic
How it works
From open question to clear next move.
02
AStart your free trialTesting
BSee it in actionTesting
CJoin focused teamsTesting
Compare the options
Bring the landing pages, pricing, concepts, or messages your team is debating.
03
Variant ATop signal68-79%
Variant B45-58%
Variant C30-44%
See the signal
Get a ranked recommendation, synthetic support range, and the objections behind the result.
Capabilities
Every variant, every segment — pressure-tested against a defined audience before the budget commits.
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M
P
D
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A
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Synthetic Personas
Generate structured audience profiles from your market description, reviews, interviews, and other supplied evidence.
A
Start free trialLiveB
Read the signalC
Join the waitlistSide-by-Side Variants
Compare up to five variants in one run without splitting live traffic.
0%
Synthetic Support
68-79% rangeLive-test first
Ranked Support
Prioritize which variant to live-test first. See synthetic support ranges across every segment.
😍42%
😊31%
😐18%
😕9%
Sentiment Analysis
See the emotional response across every segment. Surface objections you never anticipated.
Power users82%
New customers64%
Price sensitive41%
Skeptics23%
Illustrative synthetic support by segment
Decision Support
Compare action signals, objections, and segment reactions across every variant and audience slice.
v1.0
Testing
v1.1
v1.2
v2.0
Pre-Launch Iteration
Iterate on product, pricing, and messaging before deciding what deserves live validation.
Use cases
One engine for the decisions your brand, product, and growth teams cannot afford to get wrong.
01
Brand & Marketing
Pre-test campaign concepts, creative, and messaging across every audience segment before media and production budgets commit. Walk into the spend decision with the objections already mapped.
02
Product & Pricing
Compare pricing, packaging, and positioning against explicitly defined buyer segments before a launch or a pricing change you cannot easily reverse.
03
Consumer Insights & Research
Augment panels and focus groups: triage dozens of hypotheses in hours, reach segments that are hard to recruit, and focus primary research where it earns its cost.
04
Agencies & Consultancies
Bring a fast, auditable pre-decision read to client recommendations, pitches, and creative reviews — across an entire client portfolio.
Why simulate first
Replace weeks of research with a read you can act on today.
Deep behavioral panels and live measurement still matter. Similate gives your team a fast, auditable first answer — so the expensive research and live spend go to the decisions that actually need them.
Traditional researchSimilate first
Time to a first readWeeks of recruiting and fieldingHours
Cost per decisionFive to six figures per studyA fraction, repeatable on demand
CoverageOne panel, a handful of questionsEvery variant, every segment, side by side
What you getA deck weeks laterA ranked decision, the objections, and an explicit no-call
Methodology
Built to survive your team’s diligence.
Synthetic audiences are only useful if you can trust them. Every Similate recommendation is auditable, version-locked, and scored against reality — so your research and finance teams can stand behind the decision.
Locked before the reveal
Each recommendation is frozen before any real outcome is known and tied to a specific model version. No grading our own homework.
Honest no-calls
When the signal does not separate, you get an explicit abstention instead of a manufactured winner.
Scored against reality
We track ranked-winner accuracy and regret on a private scorecard, reporting abstentions beside wins, and publish only when the sample is large enough to mean something.
Live measurement decides
Similate prioritizes and explains. Real traffic remains the arbiter of causal lift — we are explicit about where the synthetic read ends.
Not just a wrapper around a language model. On a frozen, de-leaked public benchmark of 1,118 real A/B headline pairs, our ground-truth-trained model beats zero-shot GPT-5 on engagement ranking — and the edge widens with the signal — see for yourself with the free copy tester. Backed by a16z Speedrun. Read the full validation protocol.
Common questions
A faster first answer, not a black box.
Which decisions is this built for?
High-stakes, pre-launch decisions with multiple plausible options and a defined audience: campaign and creative direction, pricing and packaging, positioning and messaging, product and feature concepts, and naming. The bigger the spend riding on the choice, the more the early read is worth.
Where do the simulated audiences come from?
You define the audience from your own evidence — customer interviews, reviews, CRM segments, or an explicit ICP. Similate turns that supplied context into structured, segment-level cohorts. Fidelity is always checked against real outcomes, not assumed.
How is this different from Aaru or a focus group?
It is faster and built into your decision workflow. Instead of weeks of recruiting and a deck, you compare every variant against every segment in hours, see the objections behind each number, and get an explicit no-call when the evidence does not separate. It complements deep behavioral panels and live measurement — it does not pretend to replace causal proof.
How do you keep it honest?
Every recommendation is locked before any real outcome is revealed, tied to a frozen model version, and scored on a private accuracy scorecard with abstentions reported beside wins. Live measurement remains the arbiter of causal lift. We publish performance only once the prospective sample is large enough to be meaningful.
Get started
Bring the decision your team cannot afford to get wrong.
Walk us through an upcoming launch, pricing change, or campaign. We will show you what a defined audience reveals — and exactly where the synthetic read ends and live measurement begins.