# Doximity Ask

DevFeed: [Doximity Ask](<https://devfeed.tech/articles/doximity-ask-20025.md>)

Original publisher: [Read original article](<https://technology.doximity.com/articles/doximity-ask>)

Author: Doximity

Published: 2026-06-23T09:30:00Z

Content type: article

Language: en

Sources: [Doximity](<https://devfeed.tech/sources/doximity.md>)

Topics: [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [Retrieval-Augmented Generation](<https://devfeed.tech/topics/retrieval-augmented-generation.md>), [Hallucination detection](<https://devfeed.tech/topics/hallucination-detection.md>)

Tags: [agentic](<https://devfeed.tech/tags/agentic.md>), [ai](<https://devfeed.tech/tags/ai.md>), [grounding](<https://devfeed.tech/tags/grounding.md>), [hallucinations](<https://devfeed.tech/tags/hallucinations.md>), [retrieval-augmented-generation](<https://devfeed.tech/tags/retrieval-augmented-generation.md>), [review](<https://devfeed.tech/tags/review.md>), [verification](<https://devfeed.tech/tags/verification.md>)

## AI overview

The article explains how Doximity Ask approaches reliability in clinical AI. It describes a HIPAA-compliant clinical reference platform that combines retrieval-augmented generation, validated tools, a reasoning model, citation-grounded responses, automated verification, physician-authored evaluation, and production monitoring. It argues that reliability is a system property spanning retrieval, ranking, reasoning, tool use, verification, and evaluation.

## Source excerpt

Medical AI has attracted confident claims: perfect scores, no hallucinations, a system that gracefully declines whenever the evidence runs out. But are these dimensions the right way to think about a tool that physicians use to make real-world decisions? For clinical AI, reliability is not just a question of whether an answer is correct. It is also a question of whether a physician can understand where the answer came from, evaluate the supporting evidence, and identify situations where uncertainty remains. How Doximity Ask Answers Clinical Questions Few domains face stakes as high as medical AI, where system performance can directly influence patient outcomes, clinical workflows, and healthcare professionals' decisions. Clinical reference requires traceable grounding, numerically exact doses and scores, and explicit handling of situations in which the available evidence is insufficient to support an answer. At the same time, healthcare providers often work under significant time constraints and have exceptionally high expectations for the performance and reliability of AI systems. Doximity Ask is a HIPAA compliant composite clinical reference platform for question answering at the point of care. It combines retrieval-augmented generation over a physician-governed evidence library, multi-turn agentic tool use through a fixed registry of validated calculators and structured lookups, and a post-trained reasoning model that orchestrates retrieval, tool calls, and citation-grounded generation. Automated verifiers, physician-authored rubrics, and in-product physician review form one evaluation loop that grades releases, defines training rewards, and monitors production. Reliability Is A System Property Over 150 health systems have purchased the Doximity Clinical AI Suite including 8 of the top 20 hospitals in the country, therefore reliability is paramount. The reliability of a clinical AI system depends on more than the capabilities of its underlying language model. Pro