Generative artificial intelligence (AI) has transformed the healthcare technology landscape, but as adoption accelerates, organizations are discovering that AI is only as effective as the clinical context behind it.
That reality is at the heart of the growing partnership between IMO Health and Abridge, one of healthcare’s most prominent AI-native companies.
“What we’re seeing across healthcare is that organizations don’t struggle to access AI, they struggle to give it the clinical context it needs,” said Ann Barnes, CEO of IMO Health. “The companies creating the most value are the ones finding ways to pair powerful AI with a deeper understanding of how healthcare actually works.”
Headquartered in San Francisco, Abridge is the first AI-native clinician intelligence platform trusted by more than 300 of the largest and most complex health systems in the U.S.
“IMO Health’s Knowledge Graph gives Abridge a clinically curated reference layer that we can build on instead of recreating that infrastructure ourselves,” said Kelly McDonald, Member of Product Staff at Abridge and catalyst behind the partnership. “That helped us move faster while keeping Abridge’s models, product logic, and clinician experience at the center.”
What is IMO Health’s Knowledge Graph?
At its core, IMO Health’s Knowledge Graph is a clinically grounded layer of intelligence that helps AI systems understand healthcare data the way clinicians do.
Built on more than 30 years of clinical terminology expertise, our Knowledge Graph combines terminology, ontologies, clinical relationships, code mappings, and real-world documentation patterns into a connected, queryable framework.
By capturing semantic depth and relationships among conditions, procedures, medications, laboratory findings, and other clinical concepts, the graph gives AI systems context that traditional code-to-code connections – like SNOMED CT®, ICD-10-CM, and UMLS – cannot provide on their own.
As Kerri Grizer, VP of Product Management at IMO Health, said in a recent webinar, our Knowledge Graph functions as “the clinical meaning layer your AI can use to limit hallucinations and omissions while lowering inference cost.”
Semantic grounding is the missing layer in healthcare AI
Large language models (LLMs) excel at processing vast amounts of information, but healthcare presents unique challenges. Clinical data is fragmented across specialties, care settings, terminologies, and decades of documentation practices.
“Having a semantic bridge and an understanding of that data over time is increasingly important to unlock AI’s capabilities,” said John Laursen, SVP of Product at IMO Health, during a recent podcast interview with Faces of Digital Health. He added that while AI can analyze information at scale, “its ability to understand the nuances or the semantic interpretation of that data over time is still very limited.”
By helping clinical AI interpret healthcare concepts and relationships more consistently, IMO Health enables health tech companies to spend less time building and maintaining knowledge infrastructure internally and more time developing products for health systems, payers, and others.
Schedule a brief demo to see how our proprietary Knowledge Graph can strengthen and streamline AI development.
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