Hetu.

Decision intelligence

Decision intelligence for AI agents operating in high-stakes domains.

Hetu computes the decision, verifies it, and scores its own confidence — before your agent is allowed to act on it.

A wrong answer and a right answer arrive in the same font, with the same confidence, at the same speed.

Hetu removes the model from the part where that matters. Every figure an agent sees comes from a deterministic rule or a fitted causal model. The model only writes the sentence — and only about what was already proved.

How it answers

Three attempts. Each one knows what it is allowed to claim.

Rules

Exact

Failure patterns your experts already recognise, encoded as explicit traversals. If one matches, the answer is not an estimate.

Causal model

Attributed

A fitted graph spreads the anomaly across candidate causes, with intervals it will not round away.

44% · CI 37–51
26% · CI 19–33

Language, last

Hypothesis

Three ranked guesses at most, each with a test that would settle it. Forbidden from naming a cause.

Stopping criteria, per tier →

See how it works

Watch one drop all the way to the bottom.

A question falls through the strictest method first.

Advancing automaticallyStep 1 of 3
24 rules your experts wrote downeach square is one failure pattern
No square matchedThis combination was never written down, so nothing here may answer.
The question drops to Tier 2 — and the missing rule gets logged as a gap to write.

The guard

Nothing reaches the agent until it passes every check.

Not a score bolted on afterwards. Failing one check refuses the conclusion rather than downgrading it.

The guard

one shared service
Temporal ordering
Magnitude consistency
Gate validity
Sample-size floorn=3 of 5
Label match · not reached

Conclusion refused

The first failure ends the call. Nothing downstream runs, and the label is not quietly downgraded.

  • Action held
  • Falsification test returned
  • Written to the log

Five checks in sequence, called by every tier, so there is one place to audit what verification did.

Every check, and what happens on failure →

Autonomy

Agents don't earn autonomy by being confident. They earn it by being measured.

The envelope starts closed. It widens only where measured outcomes prove the system right, and narrows on its own when they stop.

01 Constrain

What counts as a fault, what gates what, and what is never permitted, written before anything runs.

02 Circuit-break

Irreversible, fat-tailed decisions never auto-execute, whatever the confidence score says.

03 Record

Every decision generated, approved, deferred, executed and measured, in one immutable log.

04 Calibrate

Outcomes update the weights. Types that prove out move inside. Types that don't stay gated.

Envelope mechanics and ruin thresholds →

Design partners

Bring the decision you don't currently let an agent make.

We work with a small number of enterprise teams where a wrong action is expensive. We map your constraints, seed the graph with your experts, and show you the first refusal.