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The latest breakthrough in healthcare AI is here. Meet Polaris 6.0. Now 1.3x faster, the frontier model for patient care thinks while it speaks, adjusts to a patient’s tone, and debuts a new, more realistic voice with advanced clinical hearing. Hippocratic AI just announced Polaris 6.0 Ultra, a new generation of its healthcare language model that delivers six upgrades to how an AI care agent listens, thinks, and speaks. Polaris 6.0 Ultra is the first healthcare model with what we call bedside intuition: the ability to read a patient’s emotional state, think mid-speech, and decide what to say next in the same breath, without a pause the patient can hear. “In healthcare, you don’t get credit for reminding a patient. You get credit for the action they take,” said Munjal Shah, Co-Founder and CEO of Hippocratic AI. Polaris 6.0 was built from more than 323 million patient conversations, making it the only experienced frontier model for healthcare, able to operate safely and autonomously to drive patient outcomes. That experience shows. Polaris 6.0 handles the healthcare edge cases of real life, brings more human-like common sense and pacing, and delivers the kind of empathy that persuades patients. This is the next step in care: healthcare abundance.

How does a healthcare LLM really work? What makes it safe? What are tokens? Parameters? What does RL mean? AJI? RAG? Too nervous to ask? Becker's Healthcare isn't. Next week our Chief Medical Officer Meenesh Bhimani MD, MHA, Chief Science Officer Subhabrata (Subho) Mukherjee, Chief Product Officer Vishal Parikh and Director, LLM Debajyoti (Debo) Datta are sitting down with Becker's to get under the hood of how LLMs actually work for clinical care. Sept 30. Noon CDT. Register at link. You’ll learn: ➡️ How a healthcare-specific LLM differs from a general-purpose model — and why it matters for patient care ➡️ How safety is engineered in, not bolted on: safety LLMs, automated clinical critics, and human clinician oversight at scale ➡️ What medical specificity actually looks like inside a model trained on 260M+ patient interactions ➡️ What to expect — and what to demand — from any agentic AI before your organization deploys it https://lnkd.in/gvq4Gkx2

There hasn't been a better week to have a real conversation about AI and safety. Our CEO Munjal Shah sat down with Christina Farr for Second Opinion Media's Lifers podcast to do just that. Christina didn't let it stay theoretical. They talked about what safety means when you're building for patients, and Munjal walked through how we actually think about it here at Hippocratic AI. But the part we keep coming back to is this: for basically all of human history, healthcare has run on an assumption of scarcity. Not enough clinicians, not enough hours, not enough follow-up. What we're seeing with AI in healthcare today is a shift to abundance — doing the things we couldn't do before. What does that look like in practice? One example they discussed: a health system recently handed us 1,700 patients they'd already given up trying to reach for lung cancer screening. We called them. 180 came in. Nine needed advanced care. Three cancers were found. One only needed a resection — caught early enough that it didn't need to become anything worse. That's clinical abundance: better patient outcomes that weren't delivered before AI. "Healthcare AI works best on jobs no one thought to do" | Full episode is live now — link in the comments. Thank you, Christina, for driving a real conversation.

Health systems don’t need just post-discharge call. They need fewer readmissions. Reducing readmissions means staying with a patient through the entire transition home: checking symptoms, answering medication questions, engaging caregivers, coordinating follow-up and recognizing when someone needs clinical help. That takes more than one interaction. And more than one agent. Our AI Readmission Orchestrator brings together specialized AI agents across the post-discharge journey, with a supervising brain determining what each patient needs next. The goal is not to automate one more piece of the workflow. It’s to give health systems the capacity to engage every discharged patient, across the full 30 days, with the intensity and personalization needed to actually move readmissions.