Causal decisioning · Graph memory · Draft-to-live onboarding

A decision platform that reasons, verifies, and explains.

Governed causal graphs

Explainable every decision

What-if guidance

Independent verification

Live platform architecture

Live

Decision runtimeGovernance loopOnboarding

Where your team works

Every flagged case arrives with its reasoning and a suggested next step.

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What we do

Three things every decision needs.
Three things every black-box AI skips.

We tell you why

Every decision comes with the reasoning behind it. Not a number, but a chain of cause and effect your team can read, your customers can hear, and your regulator can audit.

We tell you what to do

For every flagged case, the platform suggests the most useful next action. Not 'investigate further', but a specific next step ranked with confidence.

We check our own work

Independent verifiers score every decision in parallel. If they disagree with our reasoning, we surface it instead of pretending to be sure.

Real moments

Three operators. One ordinary day.
Three flags that need an answer.

OmarCafe operations manager

9:47 PM · Bluemoon Cafe end-of-day stock review

Kitchen stock is short by 12 units on a high-volume menu item.

BEFORE · Old system: a red flag. Investigate.

WITH CAUSAL OS · Causal OS: most likely cause is an unrecorded waste movement during the dinner rush. Suggested action: recount the item, then check whether a waste entry was missed before posting the count. Confidence 87%.

Cafe Inventory Integrity

YusufSME credit reviewer

11:30 AM · borderline working-capital application

Small bakery. Borderline working-capital application. System recommends decline.

BEFORE · Old system: 'Decline. Risk score 0.42.'

WITH CAUSAL OS · Causal OS: declined because debt-to-income is 0.61. Smallest change that flips the outcome: DTI below 0.45 or eight more months of revenue history.

SME Lending

Dr. PatelPrimary-care physician

New patient · diabetes risk reads 72%

Elevated risk score with no breakdown.

BEFORE · Old system: a number on the chart.

WITH CAUSAL OS · Causal OS: top driver is HbA1c at 7.2, above target by 0.7. If brought to 6.5, estimated risk drops to 45%. First action: review medication adherence.

Diabetes Risk

Bring your own

Your data. Your problem.
Your domain in three steps.

From a raw SQL dump or spreadsheet to a live governed domain in your workspace, with your team approving every step.

01Dataset Builder

Bring your data

SQL dump, spreadsheet, or live database. Point us at it. The Dataset Builder profiles your data, suggests the right grain, and proposes the signals that matter.

02Onboarding

Approve the cause-and-effect map

The platform drafts the causal graph. You review the candidates, choose the variant, and set the thresholds before anything goes live.

03Domain Registry

Promote to runtime

Once approved, your domain joins the live workspace on the same decisioning engine as every built-in domain.

What keeps this honest

What keeps this from becoming a black box.

Every decision comes with an explanation compiled before any text is written.

Independent verifiers run on every decision. If they disagree with our reasoning, we surface it.

Nothing goes live without explicit operator approval. No silent model updates.

Bringing your own domain uses the same runtime as our built-in ones. No second-class paths.

Live today. Decision workspace, dataset builder, onboarding, and graph governance are running product surfaces. They are not slides.

Ready to get started

Open the runtime, inspect the graph, or bring your own domain.

Use the workspace to run live decisions, review graph logic, prep your data with the dataset builder, and onboard new domains in one governed system.