Causal AI,
not correlation
Get a Demo↗︎// The say-do gap
What people do,
not what they say
Most simulation platforms model what people say they will do. The output looks like research but inherits the same bias as the surveys it replaces.
Subconscious models what people actually do. Causal experiments with error bars, not sentiment summaries with confidence scores.
Our methods are public, our benchmarks are open, and our models are auditable. If it cannot be inspected, it should not be trusted with capital allocation.
Stated intent is not the same as revealed behavior. The gap between them is where capital gets misallocated.
// Methodology
How we're different
We import your actual customer data from Salesforce, HubSpot, Snowflake, or CSV. We build causal models across every attribute, price point, and persona trait. Every prediction comes with confidence intervals.
Each experiment compounds - your organization accumulates behavioral knowledge that can't be replicated by switching vendors. This is infrastructure, not a report.
Causal experiments. Confidence intervals. Benchmarked against 350+ real human studies across 20+ domains.
How approaches differ
vs Behavioral simulation platforms
They predict what people say. We isolate what causes them to act. They don't publish benchmarks. We validate against 350+ real human studies across 20+ domains - the largest behavioral AI benchmark in the world. When a board asks 'how do you know this works,' we have the answer.
vs Synthetic survey platforms
They generate synthetic opinions from generic populations. We build causal models on your actual customer data - from your CRM, CDP, or warehouse. They give you faster surveys. We give you causal maps with confidence intervals that finance teams can underwrite.
vs Marketing attribution platforms
They explain what happened last quarter. We predict what will happen next quarter - across product, pricing, and GTM. Attribution is a rearview mirror. Causal experimentation is a headlight. One justifies spend. The other allocates it.
Why teams choose us
Causal, not correlational
Bayesian models isolate what causes change. Not what correlates, not what a language model guesses - what actually drives the decision.
Your data, not proxies
We model your actual customers from your CRM, CDP, or data warehouse. Not generic panels, not synthetic populations, not prompt-generated personas.
Error bars, not opinions
Every prediction includes confidence intervals. Investment-grade research requires knowing how wrong you might be, not just what the point estimate says.
Benchmarked against humans
350+ replicated human studies across 20+ domains. 93% accuracy against real behavioral outcomes. The largest published synthetic AI benchmark in the world.
Open source and auditable
Our methods are published. Our benchmarks are public. Our models can be inspected. We are the only open-source Causal AI platform in this market.
Compounding intelligence
Each experiment trains the next. Your organization accumulates behavioral knowledge that competitors cannot replicate. This is not a report you file - it is a decision engine that learns.