Latest news with #FactsR
Yahoo
2 days ago
- Health
- Yahoo
Corti launches new FactsR system for clinical consultations
Healthcare technology company Corti has introduced FactsR, a real-time agentic reasoning system designed for clinical consultations. This system aims to lessen 'note bloat' driven by general-purpose AI by 65%, ensuring that medical records remain precise and relevant to the actual clinical conversation. FactsR stands out from traditional large language model (LLM) pipelines adapted for healthcare by utilising Corti's recursive fact-first reasoning loop. By minimising the need for post-visit edits and transforming passive transcripts into active clinical intelligence, FactsR paves the way for real-time decision support directly at the point of care. Offered as a modular API, the system enables developers to integrate clinical-grade intelligence into healthcare applications, fostering safer AI experiences. It allows for the creation of AI that delivers concise and accurate results, which clinicians can interact with during consultations. FactsR operates in four key areas. Firstly, it listens and extracts structured clinical facts in real-time, such as symptoms and medications, during the consultation. Secondly, each fact is vetted and refined through a specialised AI-driven feedback loop, ensuring accuracy and consistency. Later on, clinicians have the opportunity to review and adjust the facts, maintaining control and complementing clinical judgement. Lastly, the system generates electronic health record (EHR)-ready notes that are concise and free from irrelevant content, leading to reduced screen time and improved focus on the patient. chief technology officer and co-founder Lars Maaløesaid: 'By breaking conversations into structured clinical facts and validating each one through recursive reasoning, FactsR elevates ambient documentation into a foundation for real-time clinical intelligence. 'When AI can listen, understand, and reason with medical context, it becomes more than a scribe - it becomes a trusted collaborator. With a developer-friendly API, we're enabling any healthtech company to embed this capability directly into their applications - safely, scalably, and in minutes.' In October 2024, Corti announced a collaboration with US-based Tanner Health and its subsidiary Healthliant Ventures. "Corti launches new FactsR system for clinical consultations" was originally created and published by Hospital Management, a GlobalData owned brand. The information on this site has been included in good faith for general informational purposes only. It is not intended to amount to advice on which you should rely, and we give no representation, warranty or guarantee, whether express or implied as to its accuracy or completeness. You must obtain professional or specialist advice before taking, or refraining from, any action on the basis of the content on our site.
Cision Canada
3 days ago
- Health
- Cision Canada
Introducing FactsR™ by Corti -- the First Clinical Reasoning Layer for Ambient AI in Healthcare
Real-time, recursive, fact-first architecture reduces AI-generated "note bloat" by 65 percent and minimizes post-visit edits - transforming passive documentation into active clinical intelligence. COPENHAGEN, Denmark, June 11, 2025 /CNW/ -- Corti, the leading infrastructure layer for building clinical-grade AI in healthcare, today announced the launch of FactsR™, a breakthrough real-time agentic reasoning system for clinical consultations. Designed with ambient documentation in mind, FactsR™ reduces general purpose AI driven "note bloat" by 65 percent, keeping records precise, relevant, and tightly aligned with the actual clinical conversation. By minimizing post-visit edits and transforming passive transcripts into active clinical intelligence, FactsR™ sets a new benchmark for ambient AI in healthcare - while unlocking the path to real-time decision support at the point of care. Unlike traditional LLM pipelines retrofitted for healthcare, FactsR is powered by Corti's recursive fact-first reasoning loop - a purpose-built engine designed to surface, validate, and structure clinical knowledge in real time as conversations unfold. Delivered as a modular API, it enables developers to embed clinical-grade intelligence directly into their healthcare applications - creating safer, leaner, and more trusted AI experiences at the point of care. Why a recursive approach matters Traditional ambient solutions pipe raw transcripts through generic models after the consultation has ended, producing verbose, error‑prone summaries that clinicians spend up to three hours a week correcting. FactsR reflects a foundational shift in AI system design - from passive summarization to active reasoning. It allows developers to build AI that offers more concise, accurate results that clinicians can interact with live, in consultations and beyond. The process unfolds in four key stages: Listen and Extract in Real Time As the consultation unfolds, FactsR continuously identifies and surfaces structured clinical "facts" - such as symptoms, vitals, medications, and social history - while the conversation unfolds, live. Vet and Refine with Specialized AI Each fact is automatically reviewed and improved through an AI-driven feedback loop. If something is unclear, the system refines it until it is accurate, consistent, and ready to use - no guesswork, no clutter. Clinician-in-the-Loop Clinicians can quickly review, accept, or adjust facts as they go. Early adopters report far fewer post-visit edits and rarely need to add missing information after the consultation. This design keeps clinicians in control, ensuring that AI augments rather than replaces clinical judgment. Generate EHR-Ready Notes Once the facts are finalized, the system assembles a clean, concise summary - free from long, verbose summaries or irrelevant content. This means: Less Screen Time Early trials show that users spend minutes, not hours, on corrections Better Patient Focus Real‑time reasoning means decisions stay in the consultation, not in hindsight. Audit‑Ready Transparency Every fact carries a timestamp, confidence score, and link back to the conversation. Healthcare AI that Delivers Reduces general purpose AI driven "note bloat" by 65 percent. The innovation behind FactsR has been published together with evaluation results on the public benchmark Primock57 dataset. The evaluation shows that FactsR increases clinical completeness by 13 percent - capturing significantly more of the relevant medical information compared to traditional ambient scribes - while reducing note bloat by over 65 percent with a clinician-in-the-loop. "Corti's system already does an excellent job capturing clinical details accurately, even in natural conversation," said a beta user from an IT team in a regional Danish hospital. "But when testing this new innovation, what really stood out was the shift toward structured, recursive fact extraction. It goes beyond basic transcription to surface the right clinical facts in real time - exactly what busy clinicians need to stay focused and cut down on documentation overload." "FactsR exemplifies Corti's core philosophy: healthcare AI must be purpose-built, real-time, and accountable," said Lars Maaløe, CTO and co-founder of "By breaking conversations into structured clinical facts and validating each one through recursive reasoning, FactsR elevates ambient documentation into a foundation for real-time clinical intelligence. When AI can listen, understand, and reason with medical context, it becomes more than a scribe - it becomes a trusted collaborator. With a developer-friendly API, we're enabling any healthtech company to embed this capability directly into their applications - safely, scalably, and in minutes." Availability FactsR is offered today through a consumption‑based API with enterprise‑grade HIPAA and GDPR compliance. Developers can start for free at and access SDKs for safe and effective app building in as little as 30 minutes. A self‑hosted option for on‑prem or sovereign‑cloud deployments enters limited preview this summer. About is a research and development company building state‑of‑the‑art AI foundation models for healthcare. The company's mission is to eliminate administrative hurdles and bring expert‑level reasoning to every corner of the globe, driving down costs and improving quality of care. Corti's models integrate seamlessly into any healthcare application through SDKs and APIs, enabling vendors, providers and payers to leverage safe, cutting‑edge AI across an extensive range of clinical use cases.
Yahoo
3 days ago
- Health
- Yahoo
Introducing FactsR™ by Corti -- the First Clinical Reasoning Layer for Ambient AI in Healthcare
Real-time, recursive, fact-first architecture reduces AI-generated "note bloat" by 65 percent and minimizes post-visit edits - transforming passive documentation into active clinical intelligence. COPENHAGEN, Denmark, June 11, 2025 /CNW/ -- Corti, the leading infrastructure layer for building clinical-grade AI in healthcare, today announced the launch of FactsR™, a breakthrough real-time agentic reasoning system for clinical consultations. Designed with ambient documentation in mind, FactsR™ reduces general purpose AI driven "note bloat" by 65 percent, keeping records precise, relevant, and tightly aligned with the actual clinical conversation. By minimizing post-visit edits and transforming passive transcripts into active clinical intelligence, FactsR™ sets a new benchmark for ambient AI in healthcare - while unlocking the path to real-time decision support at the point of care. Unlike traditional LLM pipelines retrofitted for healthcare, FactsR is powered by Corti's recursive fact-first reasoning loop - a purpose-built engine designed to surface, validate, and structure clinical knowledge in real time as conversations unfold. Delivered as a modular API, it enables developers to embed clinical-grade intelligence directly into their healthcare applications - creating safer, leaner, and more trusted AI experiences at the point of care. Why a recursive approach matters Traditional ambient solutions pipe raw transcripts through generic models after the consultation has ended, producing verbose, error‑prone summaries that clinicians spend up to three hours a week correcting. FactsR reflects a foundational shift in AI system design - from passive summarization to active reasoning. It allows developers to build AI that offers more concise, accurate results that clinicians can interact with live, in consultations and beyond. The process unfolds in four key stages: Listen and Extract in Real TimeAs the consultation unfolds, FactsR continuously identifies and surfaces structured clinical "facts" - such as symptoms, vitals, medications, and social history - while the conversation unfolds, live. Vet and Refine with Specialized AIEach fact is automatically reviewed and improved through an AI-driven feedback loop. If something is unclear, the system refines it until it is accurate, consistent, and ready to use - no guesswork, no clutter. Clinician-in-the-LoopClinicians can quickly review, accept, or adjust facts as they go. Early adopters report far fewer post-visit edits and rarely need to add missing information after the consultation. This design keeps clinicians in control, ensuring that AI augments rather than replaces clinical judgment. Generate EHR-Ready NotesOnce the facts are finalized, the system assembles a clean, concise summary - free from long, verbose summaries or irrelevant content. This means: Less Screen TimeEarly trials show that users spend minutes, not hours, on corrections Better Patient Focus Real‑time reasoning means decisions stay in the consultation, not in hindsight. Audit‑Ready Transparency Every fact carries a timestamp, confidence score, and link back to the conversation. Healthcare AI that Delivers Reduces general purpose AI driven "note bloat" by 65 percent. The innovation behind FactsR has been published together with evaluation results on the public benchmark Primock57 dataset. The evaluation shows that FactsR increases clinical completeness by 13 percent - capturing significantly more of the relevant medical information compared to traditional ambient scribes - while reducing note bloat by over 65 percent with a clinician-in-the-loop. "Corti's system already does an excellent job capturing clinical details accurately, even in natural conversation," said a beta user from an IT team in a regional Danish hospital. "But when testing this new innovation, what really stood out was the shift toward structured, recursive fact extraction. It goes beyond basic transcription to surface the right clinical facts in real time - exactly what busy clinicians need to stay focused and cut down on documentation overload." "FactsR exemplifies Corti's core philosophy: healthcare AI must be purpose-built, real-time, and accountable," said Lars Maaløe, CTO and co-founder of "By breaking conversations into structured clinical facts and validating each one through recursive reasoning, FactsR elevates ambient documentation into a foundation for real-time clinical intelligence. When AI can listen, understand, and reason with medical context, it becomes more than a scribe - it becomes a trusted collaborator. With a developer-friendly API, we're enabling any healthtech company to embed this capability directly into their applications - safely, scalably, and in minutes." AvailabilityFactsR is offered today through a consumption‑based API with enterprise‑grade HIPAA and GDPR compliance. Developers can start for free at and access SDKs for safe and effective app building in as little as 30 minutes. A self‑hosted option for on‑prem or sovereign‑cloud deployments enters limited preview this summer. About is a research and development company building state‑of‑the‑art AI foundation models for healthcare. The company's mission is to eliminate administrative hurdles and bring expert‑level reasoning to every corner of the globe, driving down costs and improving quality of care. Corti's models integrate seamlessly into any healthcare application through SDKs and APIs, enabling vendors, providers and payers to leverage safe, cutting‑edge AI across an extensive range of clinical use cases. Contact: press@ View original content to download multimedia: SOURCE Corti View original content to download multimedia: Error in retrieving data Sign in to access your portfolio Error in retrieving data Error in retrieving data Error in retrieving data Error in retrieving data
