AI at ViVE Podcast

In this episode, host Sandy Vance chats with Isaiah Granet, co-founder and CEO of Bland, for a sharp and eye-opening conversation about one of the most overlooked bottlenecks in healthcare: the phone call. Bland now handles 3.5 million phone calls a week, has raised over $100 million, including a $40 million Series B, and is backed by Emergence Capital, Scale, and Y Combinator. Isaiah brings a refreshingly honest take on what it actually takes to get voice AI into production in healthcare, why most vendors are just talking about it rather than doing it, and why the security risks hiding in third-party AI dependencies should be keeping every healthcare CIO up at night.In this episode, they talk about:Most people call a call center because they are at the end of the line and cannot solve their problem any other wayThe best voice AI systems conform to the caller, not the other way aroundIntake is the fastest path to ROI for health systems deploying voice AI for the first timeBland tracks emotional sentiment, call escalation rates, and a unique metric called utterances to measure patient experience qualityBland does not use OpenAI or any third-party LLM under the hood, meaning PHI never touches an outside vendorHealth systems should demand that calls go live within 30 days and measurable automation within 60 daysA single third-party dependency, three steps removed from a vendor, recently led to a class action lawsuitAlways declare that it is an AI agent on the call; deceptive practices destroy the trust that voice AI depends onThe CIO role is becoming one of the most important in any healthcare organization, as AI decisions multiplyA Little About Isaiah:Isaiah values community, family, and impact above all else. He believes that building for impact is what makes life. In addition to being the cofounder and CEO of Bland, he also sits on the board of the nonprofit he founded, the San Diego Chill. 

In this episode, host Sandy Vance sits down with Patricia Thaine, co-founder and chair of Limina (formerly known as Private AI), for a fascinating conversation about one of the most underappreciated bottlenecks in healthcare AI adoption: the privacy of unstructured data. With a background in natural language processing and privacy research, Patricia built the company from the ground up to solve a problem most organizations did not even know they had. Today, her platform helps health systems, research organizations, and payers de-identify everything from clinical notes to ambient listening data so they can train models, share data for research, and move their AI initiatives forward without putting patient privacy at risk. If your AI initiative is stalled because of privacy concerns, this episode is exactly what you need to hear.In this episode, they talk about:80 to 90% of healthcare data is unstructured, and most organizations have no idea what sensitive information is hiding in itCloud providers require you to send your data outside your environment, and that alone is a dealbreaker for many health systemsDe-identification is not just about removing names; quasi-identifiers like age ranges, locations, and diagnoses all factor into re-identification riskThe goal is to keep re-identification risk below 0.04%, not just strip out obvious fieldsTraining AI models on real PHI creates a memorization problem where the model can regurgitate patient information in productionProvidence Health has used Limina since the early days to train patient and physician-facing chatbots safelyA mature privacy-to-AI operating model requires statisticians, product teams, IT, governance, and legal all at the tableLIMINA rebranded from Private AI because the old name kept attracting requests for on-premise LLMs, which is not what they doA Little About Patricia:Patricia Thaine is the Co-Founder & Chairwoman of Private AI, a Microsoft-backed startup that raised their Series A led by the BDC. Private AI won the Privacy Innovation Award at PICCASO 2024, was named a 2023 Technology Pioneer by the World Economic Forum, and was a Gartner Cool Vendor. Patricia is also the host of The Data Frontier podcast and was on Maclean’s magazine Power List 2024 for being one of the top 100 Canadians shaping the country.

What does it really take to get a healthcare AI product past the proof-of-concept stage and into production? In this episode of the AI at ViVE series on the BEAT Podcast, host Sandy Vance sits down with Tushar Puri, CEO of Pegasus One, and Sebastian Ouslis, Co-Founder of ChartR Health, to find out. Together, they pull back the curtain on how ChartR is building an autonomous analytics platform that lets hospitals interrogate their own data across silos in real time, and how Pegasus One's SONG framework is the foundation making it possible. From managing agent drift to the very real stakes of lagging data in sepsis care, this conversation is a masterclass in building healthcare AI that can actually go from pie-in-the-sky to impact you can quantify. In this episode, they talk about:Why most healthcare AI projects never reach productionThe real meaning behind the SONG frameworkHow data silos slow down hospital decision-makingTurning weeks of analysis into minutes with AIThe hidden cost of poor workflow integrationWhy governance must be built in from day oneThe importance of designing for real-world healthcare systemsHow ChartR enables continuous analytics across hospital dataWhat agent drift is and why it matters long termThe role of partnerships in building scalable AI productsA Little About Tushar and Sebastian:Tushar Puri is the Founder and CEO of Pegasus One, where he helps organizations build scalable AI and software products that actually make it to production. With more than 15 years in product engineering, he specializes in bridging the gap between technical innovation and real-world implementation, especially in healthcare.Sebastian Ouslis is the Co-Founder of ChartR, an AI-driven healthcare analytics platform focused on turning complex clinical data into real-time insights. His work centers on using AI to help hospitals continuously learn, adapt, and improve patient outcomes.

AI in healthcare is moving fast, but what does real, operational impact actually look like? In this episode, host Sandy Vance chats with Aditya Bansod, CTO and co-founder of Luma Health, and Michelle Winfield-Hanrahan, RN BSN MHA MSN about this very topic. They share how the University of Arkansas for Medical Sciences is scaling AI beyond the call center and into complex, high-friction workflows like fax processing and patient access. From backfilling missed appointments to transforming referral intake, this conversation dives into what it takes to build trust, move quickly, and turn AI into measurable results across an entire health system.In this episode, they talk about:How UAMS identified a high-impact, low-risk entry point for AI in call center workflowsTurning after-hours cancellations into filled appointments and improved patient accessWhy trust in the partner matters just as much as trust in the technologyExpanding from AI call handling to backend fax automationHow AI is reducing referral lag time and improving data visibilityThe power of an EHR-first strategy and working inside existing workflowsAvoiding “AI sprawl” and the challenge of managing too many point solutionsReal talk on ROI: operational efficiency, revenue lift, and happier patientsWhy success builds momentum for scaling AI across departmentsPractical advice for health systems navigating the explosion of AI vendorsA Little About Aditya and Michelle:Aditya Bansod is CTO and co-founder of Luma Health. With a lifelong passion for building software, Bansod leads Luma Health’s technical vision and strategic direction for building a Patient Success Platform that empowers healthcare providers to serve their patients better and improve healthcare outcomes. With over 15 years of experience as a product management leader developing mobile solutions at Adobe and Microsoft, and at venture-backed start-ups, Bansod made the transition from B2B software solutions to healthcare in 2015 to have a meaningful and measurable impact on how providers use mobile technologies to engage with and communicate with their patients. Michelle Winfield-Hanrahan, RN BSN MHA MSN, is a seasoned healthcare clinical operations executive with over 20 years of experience in optimizing patient access, improving patient engagement, and streamlining clinical operations. Throughout her career, Michelle has demonstrated a strong ability to lead cross-functional teams and implement strategic initiatives that enhance the patient experience, increase operational efficiency, and drive sustainable growth.In her current role as Chief Clinical Access Officer and Associate Vice Chancellor of Access at the University of Arkansas for Medical Sciences, Michelle oversees patient access and flow from both the outpatient and inpatient setting, ensuring seamless patient flow and appointment scheduling, reducing wait times, and improving overall patient satisfaction. She has spearheaded innovative solutions that leverage technology to enhance patient communication and engagement, ensuring that patients remain informed, involved, and empowered throughout their healthcare journey.Michelle is dedicated to driving innovation in healthcare operations and is committed to making quality healthcare more accessible and efficient for all.

In this episode, host Sandy Vance and Andy Fanning, the CEO & Co-founder of Optura.ai, sit down to talk about why so many healthcare organizations are making AI headlines without actually transforming anything. Andy breaks down how Optura helps payers, providers, and life sciences companies move from a scattered list of AI ideas to a prioritized, production-ready roadmap with measurable return on investment. From crowdsourcing use cases across an entire organization to aligning AI investments with executive strategy, this episode is packed with practical insight for any healthcare leader who wants AI to actually move the needle.In this episode, they talk about:Most healthcare leaders feel they are not moving fast enough with AI, despite the headlinesShadow AI is just an unmet need, and governance is the answerCrowdsourcing AI ideas from the bottom up reveals hotspots that leadership often cannot seeAligning AI use cases to existing strategic initiatives makes adoption dramatically easierPoint solutions do not share context, and that missing context is where the real value livesReturn on AI investment requires defining what value actually means for your specific organizationAgentic AI is the next big wave, and organizations need to decide where they sit on the risk spectrumTrust at the frontline is built by showing workers how AI follows their own standard operating proceduresIf finance cannot see the ROI, they will conclude that AI does not workA Little About Andy:Andy is the Co-Founder and CEO of Optura.ai, where he's on a mission to help healthcare organizations stop dabbling in AI and start seeing real returns from it. His team built an AI Orchestration Platform designed from the ground up for healthcare, giving organizations the infrastructure, trust, and clarity to turn AI ambition into measurable ROI.The platform does it all in one place: spotting high-value AI opportunities, building and deploying custom agents, unlocking data without the ETL headache, auto-generating workflows from existing SOPs, and tracking return on AI investment in real time. No black boxes, no guesswork. Just AI that actually proves its worth.

In this episode, host Sandy Vance sits down with Adam Kamor, Co-founder and Head of Engineering at Tonic.ai, to tackle one of the most pressing challenges in healthcare's AI adoption: what to do with sensitive data you legally cannot access. Adam breaks down how Tonic AI helps healthcare organizations de-identify and synthesize unstructured data so they can train AI models safely, stay HIPAA compliant, and actually unlock the value sitting behind their firewalls. If your organization is eager to build AI-powered workflows but unsure how to handle patient data responsibly, this episode is a must-listen.In this episode, they talk about:Most valuable healthcare data is too sensitive to use for AI training without de-identificationHIPAA is actually an advantage because it gives organizations a clear roadmap for safe data useTonic Textual replaces PHI in unstructured documents with realistic synthetic valuesSynthetic data must closely mirror real data for AI models to perform well in the fieldIf a model is trained on PHI, it risks regurgitating patient information in outputsPrivacy compliance should be addressed at the start of an AI project, not as an afterthoughtMany organizations do not realize solutions already exist to help them use their data safelyA Little About Adam:Adam manages the team creating Tonic Textual, Tonic.ai's platform for unstructured data redaction and synthesis. He has spent the last 12 years as a leader at the intersection of data privacy, AI, and software engineering.

In this episode, Rajkumar Thirunavukkarasu, SVP & Head of Healthcare Provider Business at Tech Mahindra , and LaDonna Sweeten, EHR Practice Lead at The HCI Group, a fully owned subsidiary of Tech Mahindra, discuss how health systems can transform their EHR from a static system of record into a dynamic performance engine.The conversation also highlights a unique market differentiator: the combined strength of The HCI Group’s deep EHR and provider-focused expertise with Tech Mahindra’s global technology scale, engineering depth, automation capabilities, and innovation track record. Together, this partnership brings end-to-end capabilities—from EHR optimization and managed services to advanced data engineering, AI integration, and enterprise digital transformation—delivered at scale with measurable outcomes.Listeners will gain insight into how leading organizations are moving beyond implementation toward sustained transformation—leveraging global innovation, cross-industry engineering excellence, and healthcare-specific expertise to drive lasting value.In this episode, they talk about:HCI Group grew from staff augmentation to a full solutions provider after the Tech Mahindra acquisitionMany providers aren't fully utilizing EHR systems despite heavy investmentProviders face simultaneous pressure from workforce shortages, shrinking margins, and new regulationsHCI and Tech Mahindra use each org's own data to tailor strategy rather than a one-size-fits-all approachAI is set to significantly disrupt revenue cycle managementAmbient listening technology is reducing the clinician documentation burdenEnd-to-end workflow reimagination is recommended over isolated AI pilotsPatients now expect the same seamless experience from healthcare as they get from retailersHouston Methodist's new campus was cited as a model for automated, frictionless clinical workflowsValue-based care is now mandatory, making urgent AI adoption a necessity not a choiceA Little About Rajkumar: Raj T is a dynamic and accomplished business leader with over two decades of global experience in managing high-impact client relationships and driving growth in the healthcare technology space. Currently, Raj is serving as SVP & Head of Healthcare Provider Business at Tech Mahindra, where he leads strategy, delivery, and innovation for some of the world’s leading healthcare organizations. Raj's collaborative leadership style and results-driven mindset have consistently delivered value to clients, making him a trusted advisor in the healthcare technology ecosystem. Raj is passionate about harnessing technology to improve patient outcomes, streamline provider operations, and enable data-driven decision-making across the care continuum.and LaDonna:LoDonna leads enterprise healthcare technology strategy and delivery for health systems nationwide. She specializes in EHR transformation, workflow optimization, managed services, and digital enablement, partnering with executive leaders to ensure technology investments drive measurable clinical, operational, and financial impact. LaDonna uses data and best-practice benchmarks to identify performance gaps, prioritize high-value opportunities, and design targeted improvement roadmaps. She then applies structured governance and performance monitoring to mitigate risk and ensure intended benefits are realized. Her passion is helping provider organizations transform their EHR from a system of record into a data-informed performance engine that supports fiscal sustainability and provider resilience.  She understands that in today’s margin-compressed and highly regulated environment, optimization has to be measurable and sustainable, not just aspirational. 

In this episode, host Sandy Vance chats with Hari Bala, the Chief Technology Officer for Health Information Systems at Solventum. Together, they explore how healthcare organizations can build trust and confidence around AI adoption, drawing on insights from Solventum’s recent global survey of healthcare professionals.The research highlights a growing demand for AI alongside concerns that innovation could increase pressure on clinicians. Hari shares practical perspectives on how AI can support rather than overshadow providers, improve efficiency without compromising quality, and help organizations introduce new technologies in ways that feel safe and sustainable. Listen to learn how leaders can ensure clinicians feel comfortable incorporating AI into their daily workflows while improving the overall patient experience.The three key trust factors and why trust is the foundation for AI adoptionWhy trust is the currency of successful implementationThe role of AI in improving patient care and clinician efficiencyHow speed and quality can improve together rather than competeKey findings from Solventum’s healthcare AI adoption surveyThe cultural and mindset shifts required for successful implementationThe impact of AI on the patient experienceHow leaders can evaluate potential technology partnersHari Bala joined Solventum as Chief Technology Officer for Health Information Systems in May 2025. He brings more than 25 years of experience building scalable, distributed systems using generative AI, data science, analytics, and machine learning across healthcare, cloud, and security.Before Solventum, Hari led AI, data, analytics, and cloud transformation initiatives at GE Healthcare and Oracle Cerner. At Oracle, he helped establish the AI Services organization and led development of the Health Data Intelligence and Analytics platform, a near real-time, cloud-based population health solution, while advancing AI and machine learning tools for clinical use.Earlier in his career, Hari spent nearly 19 years at Microsoft in leadership roles across Azure and several core enterprise technologies.In this episode, they talk about:A Little About Hari:

In this episode, host Sandy Vance and Ted Dinsmore discuss the ever-evolving role of AI in healthcare, industry trends, challenges, and solutions. They explore the concept of agentic AI and the Model Context Protocol (MCP), which aims to enhance data integration and efficiency in healthcare systems. They also highlight the importance of building trust in AI solutions, particularly in rural healthcare settings. Listen in to learn how SphereGen is addressing these challenges through innovative AI implementation approaches.In this episode, they talk about:Latest AI trend: agentic AI and bots, and MCP in the healthcare industryMCP allows us to speed up that integrationTrust is a huge issue when you're having an impact on the patientThe benefits of using MCP for hospitals and patientsThe concerns about the changes and cuts to rural healthcareThe most common use cases when transitioning: eligibility, prior authorization, and denials managementThe effects on how healthcare systems are doing business with EHRsNext big use cases and what’s coming up nextSolving challenges in rural healthcare over the next few yearsHow rural healthcare and homecare are tiedAt the end of the day, it’s all about how AI can help free up time for peopleA Little About Ted:Ted Dinsmore is the President of SphereGen Technologies, located in New Haven, Connecticut, Toronto, Canada, and Pune, India. SphereGen is a software consulting firm that develops and supports custom software solutions for clients in AI and Automation, Application Development, and Extended Reality (AR, VR, MR). His experience in the world of IT spans over 30 years.When Ted started his first consulting firm, he became invested in developing and supporting Microsoft solutions for large multinational companies. Wanting to stay at the forefront of emerging technologies, his current company, SphereGen, embraces the world of AI/Automation and Mixed Reality (MR). SphereGen focuses on improving processes for healthcare organizations by leveraging innovative technologies, along with partners UiPath and Microsoft, to solve business problems.

AI is revolutionizing how health information is managed. Utilizing sophisticated algorithms, it can assist professionals in making more informed decisions. For instance, optical character recognition (OCR) can read and interpret medical records, identifying potential compliance issues and ensuring every page represents the correct patient. In this episode, host Sandy Vance chats with Anupriyo Chakravarti, the Chief Technology and Product Officer at Verisma, about how healthcare organizations can use intelligent automation to reduce risk and uncover compliance gaps in order to free staff to work at the top of their license. In this episode, they talk about:What Verisma can do for healthcare organizationsUse case examplesSome of the risks Verisma mitigates by finding missteps like unauthorized disclosures AI is taking over the world of informaticsEnabling people to work at the top of their license is criticalPeople are not anti-AI, they are anti-opacityA Little About Anupriyo:Anupriyo Chakravarti joined Verisma Systems, Inc. in 2017 as the Senior Vice President of Research and Development. Anupriyo brings 25 years of experience as a highly effective leader in healthcare IT product management and software development for Fortune 500 companies and startups. Anupriyo joined Verisma after serving as vice president of product management and marketing at McKesson, where he led the product management and marketing functions of the Extended Care Services (ECS) business unit. Before McKesson, he worked for 11 years at Surgical Information Systems (SIS), where he led software development, and ultimately product management, to deliver solutions for the surgery and anesthesia departments at health systems and ambulatory surgery centers. Prior to working with SIS, Anupriyo worked for Arthur Andersen, Ryder Dedicated Logistics, IBM and TATA Motors. Anupriyo has a bachelor’s degree in mechanical engineering from IIT Roorkee in India.   

The data necessary to achieve the promise of precision medicine are now available with low-cost whole-genome sequencing, microbiome analysis, proteomics, and other large datasets. Bioscope has developed a team of AI personas to help clinicians realize that promise in a way that will revolutionize the practice of medicine.In this episode, Sandy Vance speaks with Don Brown, MD, Founder and CEO of Bioscope, about how AI and large-scale biological data are converging to make precision medicine practical for clinicians. They explore Don’s entrepreneurial journey, the origins of Bioscope, and how a subscription-based, clinician-first approach is shaping the future of personalized care.In this episode, they talk about:Don Brown’s unconventional journey from double-wide to CEO of a groundbreaking companyThe inspiration behind founding Bioscope and the problem it was created to solveHow Don’s “entrepreneurial bat signal” attracted talent, partners, and early momentumWhy Bioscope began by partnering with concierge medical practices rather than large health systemsHow Bioscope’s per-patient, per-year subscription model works in practiceReal-world use cases and early case studies demonstrating clinical impactWhat the current early rollout looks like and where Bioscope is headed nextA Little About Don:Don Brown, MD, is a serial software entrepreneur, physician, and leader in precision medicine. Over his career, he has founded and scaled multiple groundbreaking technology companies, including Software Artistry, Interactive Intelligence, LifeOmic, and most recently Bioscope.AI. His companies have collectively generated billions in value through public offerings and acquisitions by organizations such as IBM, Genesys, and Fountain Life. In addition to his entrepreneurial work, Don is an active advisor, investor, and philanthropist, including a $30 million gift that established the Brown Immunotherapy Center at Indiana University School of Medicine.Don holds a bachelor’s degree in physics and a master’s degree in computer science from Indiana University, an MD from Indiana University School of Medicine, and a master’s degree in biotechnology from Johns Hopkins University. A lifelong learner, he is fluent in multiple languages, an instrument-rated pilot, an avid outdoorsman, and the author of Understanding Life. He currently serves as Founder and CEO of Bioscope.AI, where he is focused on transforming how clinicians use data to deliver personalized care.