Penguin Ai

Thank you Jason Barry at Digital Health Wire for including Penguin Ai in your run down of "big" news at the HLTH Inc. conference last week, calling out our strategic partnership with UPMC Enterprises and their ahavi platforn to build and refine our Small Language Models (SLM)s Check out his full post here: https://lnkd.in/gwCShEmp Shout out to Fawad Butt, Mark Caron, CHCIO, FACHE, Terry McMann, Kishore Ayyadevara, Vamsi Bhandaru, Srinivas Raju Rudraraju, Prassanna Venkatesh, Nagabhushanam Katikireddi, Sree Harsha A., Missy Krasner, Peter Longo, Abigail Crenshaw, Jenna Garbars

Thank you HIT Consultant Media for covering our strategic partnership with UPMC Enterprises Check out full article here: https://lnkd.in/gjFp7xvU Fawad Butt, Mark Caron, CHCIO, FACHE, Peter Longo, Terry McMann, Mike Espy, Missy Krasner, Abigail Crenshaw, Jenna Garbars, Kishore Ayyadevara, Vamsi Bhandaru, Srinivas Raju Rudraraju, Prassanna Venkatesh, Nagabhushanam Katikireddi, Sree Harsha Ankem  

Thank you to Pittsburgh Post-Gazette for covering our strategic partnership with UPMC Enterprises and our use of the Ahavi data platform at the HLTH Inc. conference this past week. Great description of one of our AI Agents for Prior Authorization and how our CEO, Fawad Butt is framing how AI can help: ➡️ Claims adjudication, which includes pre-authorization of some drug prescriptions and medical procedures, cost health care providers over $25.7 billion. Labor costs make up about 90% of these expenses, with average administrative processing costs increasing to about $57.23 per claim. ➡️ The average patient generates four to six pre-authorization requests from insurers a year, which can be simple if they involve a particular medication. However, getting approval for payment from an insurer for more complex procedures can drive up the cost of resolution. ➡️ The improvement with AI can be dramatic. If it takes 25 minutes to review a claim, we can bring that down to three minutes or less. There’s an opportunity to push that knowledge closer to the providers. Check out the full story here: https://lnkd.in/gKyMUAu2 Fawad Butt, Mark Caron, CHCIO, FACHE, Peter Longo, Abigail Crenshaw, Terry McMann, Missy Krasner, Kishore Ayyadevara, Vamsi Bhandaru, Prassanna Venkatesh, Srinivas Raju Rudraraju, Nagabhushanam Katikireddi, Sree Harsha Ankem  

Thank you Alexis Kayser at Newsweek for doing a sit down with our CEO, Fawad Butt, in the weekly newsletter in the Pulse Check section, Executive Perspectives on key industry issues https://lnkd.in/gnMrdmXt Thanks to: Thanks to: Mark Caron, CHCIO, FACHE, Missy Krasner, Peter Longo, Abigail Crenshaw, Jenna Garbars, Terry McMann, Kishore Ayyadevara, Vamsi Bhandaru, Srinivas Raju Rudraraju, Mike Espy, Kristina Simmons, Imraan Ahmed

Thank you to John Lynn, at Healthcare IT Today for interviewing our CEO, Fawad Butt at HLTH Inc. 2025 being before his panel with UPMC Enterprises and Abridge about our Ahavi Partnership - building AI models with real world data. Check out full interview here. https://lnkd.in/gXVpxQMe Thanks to: Mark Caron, CHCIO, FACHE, Missy Krasner, Peter Longo, Abigail Crenshaw, Jenna Garbars, Terry McMann, Kishore Ayyadevara, Allison Heinrichs Hydzik, Vamsi Bhandaru, Srinivas Raju Rudraraju

2nd Day of the HLTH Inc. conference, and the Penguin Ai team is in Vegas speaking on panels and walking the floor. Check out this article in MedCity News from our CEO, Fawad Butt talking about Large Language Models (LLMs) vs Small Language Models (SLMs). Here's the TLDR: THE PROBLEM: ➡️ LLMs are already peaking. Why? The internet data these models are built on has already been scraped, cleaned, and retrained over and over again. LLMs aren’t failing for lack of data — they’re failing because they don’t use the right data. ➡️ Think about what’s needed in healthcare: claims, medical records, clinical notes, billing, invoices, prior authorization requests, call center transcripts — the information that actually reflects how businesses and industries are run.  The real gold mine of intelligence is in private enterprise data that sits locked away. ➡️ Instead of confronting the limits we’re already seeing with LLMs, the industry keeps scaling up — pouring more compute and electricity into these models. Despite all that power, the results aren’t getting any smarter. THE SOLUTION: ➡️ Small language models are the future. The way forward isn’t bigger models. It’s smaller, smarter ones. SLMs are designed to do what LLMs can’t: learn from enterprise data and focus on specific problems. SLMS are: 🟰 Efficient 🟰 Domain Specific 🟰 The fit enterprise workflows ➡️ Until models can train on enterprise data, they’ll always run out of fuel. You can stack parameters, add GPUs, and pour electricity into bigger and bigger models, but it won’t make them smarter. The way forward is to fix the data problem and build smaller, smarter models that learn from the information enterprises already own. https://lnkd.in/gws5iP6c Fawad Butt, Missy Krasner, Peter Longo, Mark Caron, CHCIO, FACHE, Kishore Ayyadevara, Vamsi Bhandaru, Srinivas Raju Rudraraju, Abigail Crenshaw, Jenna Garbars, Mike Espy, Nagabhushanam Katikireddi, Prassanna Venkatesh, Terry McMann, Imraan Ahmed, Kristina Simmons

https://lnkd.in/gfP7PMim

Thank you UPMC Enterprises for covering our partnership on your corporate blog and for selecting us as one of your first AI strategic partners to work on the Ahavi data platform to help train groundbreaking new healthcare AI models. Here are the highlights: ➡️ UPMC selected Penguin Ai as a strategic data partner because of their enterprise-grade platform, which is uniquely designed to support health care initiatives - specifically its comprehensive governance and bias correction. ➡️ A complete platform, Penguin Ai combines AI tooling with proprietary language models and out-of-the box digital workers and agents to address back-office workflows. The platform enables customers to get their data ready for AI, use pre-built health care generative AI models via APIs, or start with an out-of-the-box solution in areas such as medical coding, prior authorizations, claims adjudication, appeals management, risk adjustment, medical chart summarization, and payment integrity. ➡️ The collaboration between Penguin Ai and UPMC Enterprises represents a pivotal step toward more intelligent, patient-centered health care. By combining cutting-edge AI capabilities with rich, diverse clinical data, this collaboration can enable more accurate predictions, faster decision-making, and more streamlined workflow. Read the full story here from UPMC Enterprises: https://lnkd.in/geFqZ2tp Thank you to the entire UPMCE team: Jeff Jones, Stuart Ingram, Stacy Norman, Ken Howard, Nicholas Reed Shapiro, Craig B., Maryam Jalal. Shout out to the Penguins making this partnership happen: Fawad Butt, Missy Krasner, Mark Caron, CHCIO, FACHE, Kishore Ayyadevara, Prassanna Venkatesh, Nagabhushanam Katikireddi, Srinivas Raju Rudraraju, Vamsi Bhandaru, Abigail Crenshaw, Terry McMann, Mike Espy, Jenna Garbars, Peter Longo

Big news! Penguin Ai has announced a strategic partnership with UPMC Enterprises to accelerate the next generation of health care AI innovation. Through this collaboration, we’ll work within UPMC’s new Ahavi™ data platform — a secure, de-identified, real-world environment that lets us build, train, and test health care AI models faster and more effectively. By working with one of the largest academic medical centers and insurers in the country, we get secure access to de-identified holistic and real-world data to train groundbreaking new AI models that will transform health care workflows and improve outcomes for patients. Our first (2) projects include: ➡️ Patient 360, which gives physicians a concise snapshot of a patient’s history before each visit. ➡️ Enhanced Prior Authorization, which refines our current prior authorization Small Language Model (SLM) and Agent to improve the overall review process for clinicians, insurers and, ultimately, patients. ...And there are many more to come as this partnership marks the beginning of a long-term collaboration between UPMC Enterprises and Penguin Ai. Both organizations are committed to working together to build patient and provider centered AI solutions that address the unique challenges of the health care industry. We’re beyond excited to be working with one of the nation’s leading Academic Medical Centers. This represents a significant step forward in our mission to revolutionize health care through AI. Thank you to Jeffrey Jones, Ken Howard, Stuart Ingram, Deepan C Kamaraj, Stacy Norman, Andrew Adrian-Karlin, Nicholas Reed Shapiro, Craig B., Maryam Jalal and the entire UPMC Enterprises team. Shout at to Fawad Butt, Missy Krasner, Kishore Ayyadevara, Vamsi Bhandaru, Srinivas Raju Rudraraju, Prassanna Venkatesh, Nagabhushanam Katikireddi, Mark Caron, CHCIO, FACHE Peter Longo, Abigail Crenshaw, Jenna Garbars, Mike Espy, Terry McMann for getting this partnership up and going. #RealWorldData, #HealthcareAI, #EthicalAI Read the full announcement here: https://lnkd.in/gpvG8ua4

Penguin Ai Announces Strategic Partnership with UPMC Enterprises to Advance Health Care AI Innovation https://ow.ly/VIWi50Xcure #MachineLearning #AdversarialAI #SmartAI #AI #EnterpriseAI #GenerativeAI #GenAI #MLAlgorithms #DeepLearning #AIResearch #AIRevolution