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John Snow Labs, a healthcare AI company, today announced that its Medical LLMs have been named a winner in FoundryCo.’s InfoWorld Technology of the Year Awards 2025, recognizing the most innovative and impactful technologies shaping enterprise IT.
The annual award program spotlights the products redefining software development, cloud computing, data analytics, DevOps, and AI. John Snow Labs’ Medical LLMs were selected for their industry-leading accuracy and real-world clinical impact, delivering domain-specific AI that is safe, compliant, and production-ready for healthcare and life sciences organizations.
“Artificial Intelligence is reshaping products across the technology landscape, often in surprising ways,” said Executive Editor Doug Dineley, InfoWorld. “Our 2025 Technology of the Year Award winners are the products at the leading edge of innovation — the ones putting the power of AI to practical use for enterprises.”
Purpose-Built for Healthcare
John Snow Labs’ Medical LLMs provide healthcare organizations with domain-specific performance unmatched by general-purpose models. Trained exclusively on curated biomedical literature, clinical guidelines, EHR notes, and life sciences data, the models deliver best-in-class accuracy across clinical reasoning, diagnostics, medical summarization, biomedical research comprehension, and genetic analysis.
Peer-reviewed research shows that the models consistently outperform GPT-4.5 and Claude 3.7 by 61–200% in factuality, clinical relevance, and conciseness, while operating at just a fraction of the cost. With more than 2,500 pre-trained medical models, seamless on-premise or private cloud deployment, and enterprise-grade security, organizations gain AI that is both high-performing and compliant with HIPAA, NIST AI RMF, CHAI, the EU AI Act, and other regulatory frameworks.
Industry Leadership through Accuracy and Trust
Healthcare organizations face two primary challenges when adopting AI:
domain specificity and regulatory compliance. John Snow Labs’ Medical LLMs solve both. General-purpose LLMs often hallucinate or misinterpret specialized clinical language. In contrast, Medical LLMs are engineered for healthcare workflows, consistently outperforming frontier foundation models in peer-reviewed papers on real-world clinical tasks.
Additionally, while most cloud-based LLMs require sending PHI outside the organization, John Snow Labs’ privacy-first architecture enables fully isolated deployment. Customers can keep all sensitive data, including protected health information, behind their firewalls, without sending data or prompts to a third-party API.
Proven Impact with Renowned Healthcare Organizations
Medical LLMs have already been deployed by the world’s largest healthcare systems, pharmaceutical companies, payers, government agencies, and research institutions. More than 80 public case studies showcase the models’ real-world value, including Providence St. Joseph Health, Roche, The U.S. Veteran’s Administration (VA), Ohio State University, Cigna, and many others.
John Snow Labs’ Medical Language Models deliver:
- 80% faster data abstraction
- 85% lower operational costs
- Peer-reviewed, state-of-the-art accuracy
- Fully private, high-compliance deployment
- Proven scalability in real-world production systems
“Being recognized by the InfoWorld Technology of the Year Awards reinforces our mission to deliver trustworthy, domain-specialized AI that improves patient care while keeping data private and secure,” said David Talby, CEO, John Snow Labs. “This award highlights the impact our Medical LLMs are having in the real-world, encouraging safer and more effective AI adoption.”
