Teaching a Clinical Multi-Agent System to Say I Don’t Know

This talk demonstrates a clinical AI system that avoids confident errors by abstaining when unsure, separating evidence insufficiency from out-of-distribution cases.

Overview

Serelora is a multi-agent clinical reasoning system that abstains on cases outside its calibrated zone rather than generating confident-sounding answers. The demo walks through three real cases live. In the first, every agent converges and the system commits to a coded diagnosis with a treatment plan and a patient narrative. In the second, agents disagree on the differential and the system surfaces the disagreement to the clinician rather than averaging it away. In the third, the case sits outside the homeostenotic tolerance band of our Clinical Complexity Risk score and the system formally abstains and routes the case to human review. During the talk I will show the orchestration graph, the multi-agent conflict-detection logs, the math of the CCR tolerance band, and the structured chart artifact the system produces when it does decide to commit.

Tech stack