A 68-year-old patient with Type 2 Diabetes asks your AI:
"What should my HbA1c target be?"
Four authoritative sources. Four different answers.
Click each source to understand why they disagree. This isn't a bug in your data—it's healthcare.
Each source is authoritative. Each has valid reasoning. Each optimizes for something different.
Pick a source. See what happens.
In healthcare, every choice has downstream consequences. There's no "right" answer—only documented decisions with clear rationale.
Conflict resolution happens before ingestion, not at query time.
Clarity detects conflicts when documents enter your system—not when a clinician asks a question.
When you add ADA guidelines to your knowledge base, Clarity identifies that they conflict with your existing AGS and CMS documents on 47 clinical topics.
Semantic analysis, not keyword matching. Clarity understands that '< 7.5%' and 'avoid aggressive targets' are in tension.
A clinical informaticist reviews each conflict with both sources side-by-side. They make an explicit decision: 'For patients over 65, follow AGS. Document rationale.'
The decision is captured, timestamped, and attributed. Not buried in a prompt. Not implicit in retrieval order.
The resolution becomes part of your organizational knowledge: 'Patient.age > 65 AND condition = Type2Diabetes → HbA1c target = individualized per AGS, reviewed by Dr. Chen, 2024-01-15.'
When your AI answers the question, it returns the resolved policy with full provenance—not a guess.
The conflict isn't a problem to eliminate.
It's a decision to document.
Healthcare sources disagree because they optimize for different things. That's not going to change. What can change is whether your AI has an explicit, auditable resolution—or whether it guesses every time.
See how Clarity resolves conflicts in your documents.
Bring your own clinical guidelines, or use ours.