AI, held to the standard of care.

Simulated patient environments for post-training. Every reward is checked against the clinical guideline, so models learn the standard of care, not shortcuts.

For labs post-training health models. The same environments test any agent before it reaches patients.

Marguerite D., 67Heart failure, type 2 diabetes
Day 0 of 30
Week 1
Week 2
Week 3
Week 4
Week 5
  • Agent A · v2.4
    Agent A · v2.4, Day 0
  • Agent B · v2.3
    Agent B · v2.3, Day 0
Decision met the guidelineMissed it
Agent A
Agent B
Guideline checkEvery decision is checked against the guideline that governs it.

Do your agents meet the bar from

  • USPSTF
  • CDC
  • CMS
  • ACC/AHA
  • ADA
  • Joint Commission
  • HEDIS
  • NCQA
  • AHRQ
  • IDSA
  • WHO
  • NICE

Train health models on rewards they can’t game.

Benchmarks test what a model knows. Ordinal tests what it does across a patient’s 30 days, and every reward traces to a written rule.

Held-out exam · patients the model never trained onDecisions that met the guideline, before and after two weeks of training
Before0%
After two weeks0%
And the shortcut it found on the way · our own training run, starting
The score went upShare of decisions that met the guideline
–
Score–
CategoryScore
Round 1no data
Round 2no data
Round 3no data
Round 4no data
Round 5no data
Because the model stopped askingQuestions asked per patient
–
Questions–
CategoryQuestions
Round 1no data
Round 2no data
Round 3no data
Round 4no data
Round 5no data
Checking each round’s decisions against the rules…
Plugs into your harness
A Gymnasium-style API: reset, step, reward. Runs alongside your own models.
Held-out patients
Gains are measured on patients the model never trained on: 70% to 85% in two weeks.
Rewards it can’t game
Each reward cites its rule and guideline, so benchmaxxing shows up as a flag, not a score.

Every decision, checked against the guideline that governs it.

Patients hold back facts until the agent asks. Each decision gets a verdict and a reward from a written rule that cites its guideline, the same on every run.

Simulated patient · Marguerite D., 67, heart failure · day 11
Guideline check
Escalate rapid weight gainWhen weight rises 2 kg or more in 3 days, escalate to the care team within 1 day.Source: ACC/AHA heart-failure guideline
Waiting for a decision

The same environments test any agent before it reaches patients.

For health systems and agent builders. Compare vendors on your own patients, or check every version before you ship it.

Health systems: compare vendorsAgent builders: check each version
Post-discharge follow-up · each agent run on 500 simulated patients like yours
AgentMet the guidelineHarmful mistakesYearly savings (est.)Safe to deploy?
Vendor A’s agent0%$0.0–0.0MChecking…
Vendor B’s agent0%$0.0–0.0MChecking…
Your team today0%Baseline—
Why Vendor B’s agent is not yet safeTwice it logged a rapid weight gain without escalating it. Both patients were admitted with heart failure. Rule: escalate rapid weight gain · ACC/AHA heart-failure guideline

Your agents are overdue for a screening.