Causal experiments for business decisions

Test the decision.
Then make it.

Compare a price, product, or message in a causal experiment before you commit capital.

Test a decision↗︎See proof

// Users

Used across category leaders.

// Category

See what each option causes.

Effect. Uncertainty. Action.

Subconscious runs randomized experiments on a simulation of your market, validated against real human behavior.

You get the estimated effect of each option, the confidence interval, and a clear next move.

// Decisions

Three decisions. One test.

Price

Compare price and package options before revenue is at risk.

Product

Test which feature, offer, or assortment deserves capital.

Message

Measure which claim changes customer choice before launch.

// Causal decision API

Launch the story patients, prescribers, and payers actually move on.PharmaFind the causal message behind peak share before launch money is gone.Stop guessing what deserves shelf, spend, and space.CPGModel the behavior behind trial, trade, pricing, and repeat before the category decides for you.Grow ARPU without triggering churn.Telecom / MediaSee which pricing, bundle, and audience moves create lift instead of backlash.Win the room before the opposition defines it.PolicyKnow which message changes minds, turnout, and trust while there is still time to act.

// Method

From question to action.

// Price decision

01
Define
Name the options and the outcome.
02
Connect
Bring the evidence that defines the market.
03
Test
Randomize the intervention.
04
Decide
Compare effect and uncertainty.

Options: $39 / $49 / $59
Outcome: Customer choice
Effect: Estimated lift
Range: Confidence interval
Decision: Act, revise, or stop

// Customers

Customer evidence.

A space tourism MVP shaped against a segment of fewer than 30,000 people worldwide, saving $8M in aerospace research.

“Subconscious.ai augmented the [client's] space tourism MVP in minutes. No wasted iterations. Good press coverage — not price — is the primary driver in consumer preference for [the client].”

Space tourism engagement, 2026 | A commercial spaceflight leader

River City Federal Credit Union lifted auto-loan ad Result Rate 42% and avoided $40,000 in testing costs.

“We’ve been looking for ways to utilize data better to accomplish our mission of serving our community and members and are thrilled to be one of a select few organizations in the world that have access to this revolutionary technology. It’s exciting to see how harnessing the power of AI with a data-driven approach can improve campaign metrics.”

Michael Quintanilla, CFO, River City Federal Credit Union | River City Federal Credit Union

Synthetic respondents reproduced Mintel's own moisturizer conjoint from demographics alone, with no choice data as input.

“The best comparison we've done across all our work together.”

Ezeugo Chukukere, Mintel, on the side-by-side results | Mintel

// Who we are

Leadership

Proof you can inspect.

Claim. Source. Limitation.

93% replication accuracy

93% is replication accuracy: how often simulated studies reproduce the direction and outcome of the original human studies. It is a validation result, not a guarantee for a new market.

Read the paper

Public leaderboard

See current cross-domain results and failure modes.

Open the leaderboard

Customer evidence

See decisions, outcomes, and source notes.

Read case studies

Security is reviewable

Enterprise security documentation is available in the Trust Center.

Open Trust Center

// Next

Make the decision with evidence.

Bring the decision. We will show you what can be tested.

Test a decision↗︎

Test the decision.
Then make it.

Used across category leaders.

See what each option causes.