The cost of getting it wrong
Medical coding converts clinical reality into structured data, powering reimbursement, reporting, and public health decisions. Coding errors are expensive, but the human cost goes much further.
One example shows the scale of what is missed: in a recent study of Danish patient data, Corti identified three times as many suicide attempts as had been coded. The cases were all there - recorded in clinical notes, flagged in medication records - but coders, working under time pressure, had missed them. When cases go uncounted, health systems can't monitor trends, allocate resources, or design interventions. Policy fails before it starts.
Defined by frontier research
Medical coding is fundamentally a reasoning task, not a prediction problem. It involves interpreting many complexities, real judgment, and justification across thousands of codes. The American coding system alone, ICD-10-CM, has 70,000 diagnosis codes. Even worse, coding is based on guidelines that constantly evolve, making historically data-trained models inadequate.
Corti started addressing this by conducting the largest study of its kind (5.8 million patient encounters), leading to Code Like Humans, a multi-agent framework accepted to EMNLP 2025, one of machine learning's top conferences. This framework mirrors professional coders' steps: identifying evidence, reasoning through hierarchies, validating against guidelines, and reconciling ambiguity. Symphony for Medical Coding builds on this foundation to perform work like expert coders, delivering higher quality than other models at a fraction of the cost.
"Most AI systems fall short in medical coding because they treat it as labeling, not reasoning. Correct coding depends on evidence, context, hierarchy, and guideline interpretation. We built Symphony for Medical Coding to follow the same decision process expert coders use, and that is why the performance gap is so meaningful," said Lars Maaløe, PhD, CTO and co-founder of Corti.
"The methodology behind Code Like Humans is the most promising approach to medical coding we've seen. We've been co-developing with Corti because we believe specialized AI infrastructure is how this problem gets solved - and we're excited to see it move into production," added Steve West, Managing Director, Healthliant Ventures and Tanner Health.
Accuracy that can be audited
In medical coding, accuracy requires traceability, defensibility, and ease of review. Symphony for Medical Coding links assigned codes to its clinical evidence and highlights ambiguities, giving teams, compliance leaders, and auditors a clear record of code.
"Medical coding has been treated as a back-office cost center for decades. It isn't - it's the data layer that healthcare runs on. Getting it right changes what health systems can see, decide, and do," said Andreas Cleve, CEO and co-founder of Corti.
Available across the US and Europe, as one system
Coding systems vary widely, and most AI products require local fine-tuning. Symphony for Medical Coding does not. It is the first coding system designed to operate across both US diagnosis coding (ICD-10-CM) and procedure coding (ICD-10-PCS, CPT) and European coding environments without the need for local retraining.
ICD-10, maintained by the WHO, is currently available in beta as Corti expands across priority European markets, including the UK, Germany, France, and Denmark. Symphony for Medical Coding is available now through the Corti Console, integrates directly with the Corti Agentic Framework, and supports both A2A and MCP standards. Enterprise and sovereign cloud deployments are available through Corti.
About Corti
Corti is healthcare's frontier lab for clinical-grade AI. Symphony, its flagship clinical-grade AI model, powers clinical and administrative applications for EHR vendors, virtual care platforms, practice management systems, and life sciences organizations worldwide. Corti serves over 100 million patients annually across health systems including the NHS. The company is headquartered in Copenhagen with offices in New York and London. For more information, visit corti.ai.
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