Healthcare & Life Sciences
The Problem
The model includes mutually exclusive symptoms in the same hypothesis. It finalizes treatments without checking contraindications. It inherits publication bias from literature that overrepresents positive results. And it tells patients what they want to hear instead of what the evidence shows. Four harnesses. The Reasoning Harness enforces diagnostic logic. Anti-Deception forces honest patient communication. Memory tracks patient state across visits. Code verifies clinical decision support algorithms.
How Ejentum Solves It
One API call forces your model to check contraindication constraints and demand mechanistic evidence before accepting any clinical hypothesis. Confirmation bias is structurally blocked. The agent tells the patient what the evidence shows, not what they want to hear.
How Four Harnesses Protect Your Agents
Reasoning Harness
primaryEnforces biological invariants, contraindication checking, and causal mechanism verification. Blocks confirmation bias in diagnostic hypotheses. +19.3pp on abstraction tasks. Perfect 1.000 composite on the hardest boundary-enforcement benchmark.
Anti-Deception Harness
Forces honest patient communication. Prevents minimizing symptoms to avoid difficult conversations. Blocks fabrication of prognosis certainty when evidence is ambiguous. The agent says "the evidence is unclear" instead of inventing reassurance.
Memory Harness
Tracks patient state across visits and referrals. Detects when a symptom reported in Visit 1 was implicitly resolved or worsened by Visit 3. Prevents stale treatment plans from persisting after the clinical picture changed.
Code Harness
Verifies clinical decision support algorithms, diagnostic scoring code, and dosage calculation logic. Catches the silent bugs that produce plausible but incorrect clinical outputs.
Run your next diagnostic reasoning task through the API. See how the injection forces constraint checking you did not prompt for.