HealthTech2Care (HT2C) Podcast featuring Amir M. Rahmani, Professor at UC Irvine and Co-Founder of Integrated AI Systems, which includes Centralive (Closed-Loop Platform for Clinical Research) and openCHA (Conversational Health Agents).

In this episode, Amir M. Rahmani shares how his background in computer science, IoT, and digital health research led to building platforms designed for real-world clinical research and patient engagement. He explains why so many research teams end up reinventing the wheel with every new grant, and why platforms often disappear once funding runs out.

We also cover how Centralive and openCHA address this problem by providing reusable, modular infrastructure for data capture, real-time sensing, analytics, and intervention. Amir breaks down the idea of "closed-loop" systems using simple analogies, like cruise control and navigation, to explain why continuous sensing, sense-making, and action are critical for personalization in healthcare.

This conversation explores how conversational health agents fit into closed-loop workflows, why large language models alone are often overkill for healthcare problems, and how agents can orchestrate evidence-based knowledge, validated models, and real patient data. Amir also shares how these platforms are being used across academia, RPM programs, decentralized trials, and digital therapeutics, along with what kinds of partners and pilots he's looking for next.

Timestamps:

00:00 Intro

01:05 What pulled Amir into healthcare tech, and how it led to Centralive and openCHA

04:51 What problems in academic research led to productizing Centralive

09:48 What makes Centralive different and how it simplifies sensing, EMAs, analytics, and interventions

16:02 How study teams adopt Centralive and what the grant-driven adoption path looks like

20:28 What inspired openCHA and how it supports workflows like RPM, research, and decentralized trials

30:34 What partners and opportunities Amir is looking for across Centralive and openCHA

34:12 Best way to get in touch or try Centralive and openCHA

Highlights:

- Why do most research platforms disappear when a grant ends

- How closed-loop systems enable real-time personalization

- The difference between static workflows and adaptive interventions

- Why conversational agents need evidence, not just LLMs

- Where closed-loop platforms and agents fit in clinical research, RPM, and DTx

Learn more about Centralive (https://centralive.health) and openCHA (https://www.opencha.com)

Amir M. Rahmani (Guest):

🔗 LinkedIn: https://www.linkedin.com/in/amir-m-rahmani-26555b44

🌐 Website: https://centralive.health

📺 YouTube: http://www.youtube.com/@CentraliveTeam

Bert Fernandez (Host):

🌐 Website: https://www.healthtech2care.com

🔗 LinkedIn: https://www.linkedin.com/in/bert-fernandez

📺 YouTube: https://www.youtube.com/@HealthTech2Care

Subscribe to the HealthTech2Care YouTube channel for more in‐depth conversations with healthcare innovators

#DigitalHealth #ClinicalResearch #ClosedLoop #HealthcareAI #ConversationalAI #RemotePatientMonitoring #HealthTech

HealthTech2Care (HT2C) Podcast featuring Stephen Rouse, Co-Founder and Head of Growth at Savva.AI Stephen Rouse In this episode, Stephen Rouse shares how his experience building one of the earliest FHIR apps shaped Savva's approach to consumer health technology. We unpack why multi-year hospital buy cycles pushed the team to build directly for patients, how the ONC Cures Act unlocked large-scale access to health data, and why Savva chose to build the first on-device medical LLM to prioritize privacy and security.

We also cover how Savva connects to nearly 300,000 care sites through 110+ EHRs, why keeping medical AI off the cloud matters, how Apple Health enables aggregation across wearables and devices, and how caregiver and clinician access could become a stepping stone toward real-world care escalation.

This conversation explores what it truly means for patients to own their health data and why this moment feels like a turning point for consumer-driven healthcare.

Timestamps:

00:00 Intro

01:17 Lessons from Protocol First and why hospital sales cycles pushed a consumer-first approach

03:44 How Savva unlocked scale through the ONC Cures Act and FHIR access

05:42 What it means to be an on-device medical LLM and why privacy drove that decision

08:51 How Savva aggregates wearable and Apple Health data into one experience

12:30 The caregiver and clinician vision for real-world care delivery

16:41 Beta strategy, early traction, and what's next for Savva

🔑 Highlights:

- Why four-year hospital buy cycles pushed Savva to build for consumers

- How the ONC Cures Act enabled third-party access to EHR data at scale

- What makes an on-device medical LLM different from cloud-based AI

- How Savva aggregates wearables, apps, and devices through Apple Health

- The role of caregivers and clinicians in turning raw data into action

(Guest):

🔗 LinkedIn: https://www.linkedin.com/in/rousestephen

🌐 Website: https://www.savva.ai

📺 YouTube: http://www.youtube.com/@getSavva

Bert Fernandez (Host):

🌐 Website: https://www.healthtech2care.com

🔗 LinkedIn: https://www.linkedin.com/in/bert-fernandez

📺 YouTube: https://www.youtube.com/@HealthTech2Care

🔔 Subscribe to the HealthTech2Care YouTube channel for more in‐depth conversations with healthcare innovators: https://www.youtube.com/@HealthTech2Care

#HealthTech #DigitalHealth #HealthcareAI #ConsumerHealthApp #PatientData #PrivacyByDesign #FHIR #ONCCuresAct