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Enterprise Layer Intelligence
Categories/AI Analytics/Simile
Simile

Simile

Founded by Joon Park in 2024

Simulate customer and population responses to product launches, pricing changes, and marketing campaigns

Pricing model

Demo

Rating

★ People love it

Time to value

Moderate Setup (1-3 hours)

You can use Simile to test how real customer populations react to business changes before launching them. It models consumer behavior based on large-scale human data and generative agents created by Stanford researchers. You can input your own loyalty records, customer telemetry, or survey data to run custom simulations. The system allows you to test marketing messaging, pricing strategies, and product concepts across diverse demographics. Each simulation provides confidence scores based on validation against real human responses, helping teams reduce the risk of failed launches.

What Simile does

Run simulated focus groups using synthetic consumer agentsImport proprietary customer telemetry and balance history dataCompare response rates across multiple advertising conceptsEstimate churn percentages for upcoming pricing adjustmentsCheck confidence ratings across simulated target audiencesMeasure consumer pushback regarding product policy updatesGenerative agent simulation with memory, reflection, and planning capabilitiesValidation against weekly evaluations of thousands of real human responsesCustom behavioral model training using proprietary enterprise customer dataAutomated confidence scoring showing predicted accuracy levels for each resultContinuous model refreshing to account for real-world cultural and market driftSide-by-side scenario testing for advertising, product concepts, and pricing

Pricing breakdown

Pricing model: Book a demo

Tutorials & Demos

Frequently asked

AWSAWSGoogle CloudGoogle CloudMicrosoft AzureMicrosoft Azure

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Simile, behavioral simulation, generative agents, customer simulation, synthetic research, market research, consumer behavior, product validation, pricing tests, user research, synthetic users, population simulation, Stanford AI, customer insights, focus groups