Agentic AI is changing that model.

In a new AuntMinnie op-ed, PocketHealth Co-Founder & CEO Rishi Nayyar explains why the real advantage no longer comes from network size, but from the intelligence layered on top. Agentic AI can safely operate through the same systems staff already use, without custom integrations or exclusive pathways.

Automation acts as the user and shifts the focus away from network-building and towards intelligent applications that make care safer, more transparent and better for both patients and care teams. That means faster access, lower operational overhead and a future where vendors compete on usability and insight—not the size of their network.

With health systems under growing pressure to do more with less, intelligent automation that works across disconnected systems is becoming critical infrastructure.

Read the full op-ed on AuntMinnie.

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Rishi was selected for his work advancing how patients and care teams access, use and act on imaging, and for taking on the operational barriers that slow care across health systems. After a decade of modernizing image access through patient-centric interoperability, he is now helping usher in a new era of responsible automation in radiology operations–reducing administrative burden, strengthening care coordination, and enabling more connected, efficient workflows at scale.

Congratulations to Rishi and to all honorees in the Class of 2025!

Read the full list here: radiologybusiness.com/radiology-business-forty-under-40-class-2025

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Radiology Business: Patient Adherence and Cost Reduction

Radiology Business focuses on Conductor’s measurable outcomes, highlighting how Mackenzie Health’s deployment led to improved patient adherence and significant cost avoidance. The article details how PocketHealth’s automated patient communications helped the hospital system reduce wrong-site patient arrivals by 80% and avoid $110K in annual operating costs.

Read the full story at Radiology Business 

HIT Consultant: Agentic AI for Workflow Automation

HIT Consultant takes a closer look at the technology powering Conductor, exploring how its agentic AI architecture sets it apart from traditional healthcare automation solutions. Referencing its ability to handle unstructured inputs, like faxes and messy PDFs, the article dives into how Conductor can understand and orchestrate complex, multi-step workflows across EHR, PACS and referral systems.

Read more at HIT Consultant

AuntMinnie: Administrative Labor Savings at Scale

AuntMinnie highlights how agentic AI can drive operational efficiency not just within radiology departments, but system-wide. The article shares the impact Conductor is having on healthcare organizations, where end-to-end back-office automation is driving significant labor savings.

Read the full story at Aunt Minnie

What’s Next

Conductor is designed to automate the non-clinical workflows that slow down care — from requisition intake and order creation to scheduling and patient communications. Early deployments show measurable efficiency and cost gains.

Interested in learning more? Visit pockethealth.com/conductor or book a meeting with our team at RSNA in Chicago, November 30 – December 3, 2025.

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TORONTO, November 7, 2025 – PocketHealth today announced the launch of Conductor, an agentic AI system built to automate every non-clinical step of care, from requisition intake and order creation to scheduling and appointment confirmations.

As healthcare systems across North America face rising patient volumes, shrinking staff resources and growing administrative costs, Conductor helps expand capacity without adding headcount, reduces manual errors and accelerates speed of care, while keeping patients in-network through faster, more responsive operational workflows.

Conductor does more than move data or automate tasks; it uses agentic AI to understand and orchestrate entire workflows, mirroring the nuanced steps staff already take to move information safely between systems.

“Healthcare’s biggest bottleneck isn’t clinical; it’s the manual work that lives between systems,” said Rishi Nayyar, Co-founder and CEO of PocketHealth. “Until now, automation couldn’t handle the complexity of those workflows. Advances in agentic AI—combining large language, vision and voice models—finally make true end-to-end workflow automation possible.”

Early applications of PocketHealth Conductor include: 

• AI requisition processing: Uses Conductor’s Vision Agent to process faxed and digital requisitions from receipt to order creation.
• Automated scheduling: Enables 24/7 self-scheduling through intelligent SMS, web and voice with automated confirmations and rescheduling.
• Intelligent communications: Automatically delivers patient- or provider-facing messages, forms, reminders, instructions and updates, personalized to each care context.
• Inbound call center: Manages high-volume inbound calls through conversational AI to reduce administrative workload and wait times.
• Custom workflow automation: Extends automation to any operational, repetitive task across departments within existing systems and audit trails.

Conductor applies this approach across the health system, extending beyond radiology operations through configurable [customizable] automations: It reads, validates and routes requisitions; creates orders; manages self-scheduling via voice or SMS; powers an always-on call center; and sends reminders and confirmations. Each process runs within existing infrastructure with full auditability, and only pre-approved actions are performed.

“Administrative inefficiencies are one of healthcare’s biggest hidden costs,” said Dr. Ram Chadalavada, Chief Medical Officer at PocketHealth. “When automation is designed with clinical and compliance guardrails in place, it doesn’t just save time and cost, it improves accuracy, traceability and ultimately, patient safety.”

Projected impact across radiology and broader health system operations shows substantial labor savings:

• Large outpatient network: ~1,500 daily calls handled by 18 FTEs; Conductor-enabled digital self-scheduling and inbound call deflection target a significant reduction in administrative load.
• Regional imaging system: 20 FTEs spend ~ 75% of their time manually processing faxed requisitions; automation is expected to reclaim hundreds of staff hours monthly.
• Multi-site health system: ~70% of requisitions still arrive by fax; automation frees up to 12 FTEs across sites by reducing manual entry and duplication. 

PocketHealth will be demoing Conductor at the Radiological Society of North America (RSNA) Annual Meeting in Chicago. Book a demo with our team here or visit here to learn more.

About PocketHealth
PocketHealth is the agentic AI workflow automation platform transforming health system operations. With three interconnected solutions—Conductor, Image Exchange and Patient Connect—PocketHealth automates all manual, non-clinical tasks across the patient journey, from requisition processing to inbound call management to seamless image sharing and patient engagement. As a result, providers can redeploy staff, expand margins and deliver safer, more seamless care, while patients gain the knowledge and guidance they need so follow-ups don’t fall through the cracks. PocketHealth is SOC2- and HIPAA-compliant, and is trusted by more than 900 hospitals and imaging centers across North America. Learn more at pockethealth.com.

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Radiology reports are among the most important documents in a patient’s health journey, but for most people, they’re written in a language that feels foreign.

Patients often tell us the same thing: “I can see my report, but I can’t understand it.” That gap between access and comprehension can lead to anxiety and missed opportunities to have more informed conversations with physicians.

At PocketHealth, we’ve always believed patients should have access to and ownership of their imaging records. But access alone isn’t enough. Patients also need to understand what those records say.

Introducing Report Explanations

Over the last few months, we’ve been rolling out our plain-language report explanations as a new way for patients to make sense of their radiology reports. Integrated into our Unlimited plan, this feature is already in wide use.

Nearly 100,000 patients have already used report explanations to make sense of their results. The feature provides in-depth, plain language explanations written alongside their original report, powered with AI.

As we’ve developed this feature, we’ve seen academic studies review the impact of educational tools on small groups of patients. PocketHealth is now bringing in-depth patient education to scale, and it’s already changing the way patients interact with their results.

Built with Patients and Clinicians

The report explanations feature was developed with input from patients and clinicians, and implements strict guardrails:  

• Explanations only include information included in the original report
• Language is written for a high-school reading level
• No medical advice is given if not included in original radiology report
• Clinicians regularly review explanations for accuracy and clarity 

In a world where patients often turn to Google or ChatGPT for health answers, our plain language report-explanations provide safe, contextual information that patients can trust.

What Patients Are Saying

The response has been powerful:

• “Getting a version of my report that’s easy to understand makes me feel confident discussing it with my doctor.” Marlene, PocketHealth patient.
• “It’s clear to someone who isn’t in the medical field, and saved me a lot of anxiety and panic.” Kat, PocketHealth patient.

These voices matter more than any technology milestone. They show what happens when comprehension becomes part of access: patients feel more confident, more informed and more engaged in their care.

Available Across North America

Report explanations are available to all PocketHealth patients in Canada and starting this month, U.S. providers can enable the feature for their patients as well.

This feature is already reshaping how patients interact with their imaging records resulting in less anxiety and more meaningful conversations with their providers. It’s also a step toward something bigger: reducing the non-clinical burdens that get in the way of care, so the clinical experience can take center stage. 

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In a new AuntMinnie op-ed, PocketHealth Co-Founder & CEO Rishi Nayyar shares why agentic AI is becoming the new infrastructure for interoperability. These agents act like credentialed teammates — safe, auditable, and governed by institutional policies — extending standards into the messy edges where systems don’t connect.

For providers, the impact is tangible: fewer manual clicks, less delay and greater confidence that workflows are compliant and complete.

Read the full article on AuntMinnie

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“You can give a patient a scan, but without guidance or context, it’s easy for next steps to fall through the cracks.”

Radiology Today features PocketHealth in a recent article about how AI is helping radiology teams better manage follow-ups and prevent patients from falling through the cracks.

The piece highlights how PocketHealth’s follow-up management and patient engagement tools support both patients and providers by surfacing next steps, reducing manual work, and improving continuity of care. By helping track follow-ups, streamline communication, and prompt timely clinical interventions, these tools allow radiology teams to reduce risk and strengthen care coordination, leading to more connected, patient-centered care. Co-Founder and CEO Rishi Nayyar and Chief Medical Officer Dr. Ram Chadalavada share why access alone isn’t enough and how intelligent follow-up can close critical care gaps.

Read the full article here to learn how PocketHealth is helping providers improve follow-up adherence and patient engagement.

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PocketHealth has launched Image Reader, the first feature to apply AI-powered anatomical visualization directly into patients’ imaging results. By providing visual context within a scan, Image Reader helps patients better understand what they are seeing in their images, leading to more informed discussions with providers and fewer misunderstandings about their results.

Image Reader leverages multiple segmentation models including MedSAM (Medical Segmentation Anywhere Model) that have been refined to support a patient-friendly application of medical imaging segmentation. Developed by AI scientist Dr. Bo Wang and his team, MedSAM is a model specifically designed for universal medical image segmentation across diverse modalities. Building on these capabilities, PocketHealth Image Reader identifies and transforms anatomy mentioned from radiology reports onto segmented anatomical structures in CT and X-ray scans, ultimately improving patient understanding of their medical images.

“Reviewing medical imaging results can be complex and intimidating for patients, and radiology reports often lack visual references, making it harder for patients to connect findings to their own anatomy, ” said Dr. Ram Chadalavada, Chief Medical Officer at PocketHealth. “PocketHealth has improved patient literacy around medical reports with Report Reader – now, Image Reader builds on that by automatically identifying organs and bones in scans, offering clarity that helps patients feel more confident, informed, and engaged in their care.”

Image Reader is PocketHealth’s newest feature designed to help patients interpret their imaging with greater clarity and confidence expanding PocketHealth’s patient-centered toolkit, complementing Report Reader and MyCare Navigator.

AI-Powered Anatomical Identification

PocketHealth is the first to bring AI-powered anatomical visualization directly to patients within their medical imaging records, providing a more interactive experience. Fine-tuned for generalizability, PocketHealth’s model accurately identifies anatomy across a range of imaging sources, scanner types and clinical settings by automatically detecting and labeling organs and bones within medical images.

“Medical imaging AI has primarily focused on clinical applications, but there’s an equally important opportunity to improve patient understanding,” said Dr. Bo Wang, Chief AI Scientist at the University Health Network (UHN), who led the development of MedSAM. “PocketHealth has taken an innovative approach by refining our segmentation  model  for real-world patient use. Using this technology to directly benefit patients is a meaningful step toward making medical imaging more accessible and insightful.”

Currently optimized for a variety of CT and X-ray exams with plans to expand support for additional imaging modalities, Image Reader will be showcased at HIMSS 2025 in Las Vegas (March 3-5) at the PocketHealth booth in the Patient Engagement Pavilion. Learn more about Image Reader and PocketHeath’s other patient engagement tools here.

About PocketHealth

PocketHealth is a connected care company that empowers patients to take control of their health by providing seamless access to their diagnostic imaging records. With enterprise image exchange and intelligent patient engagement solutions, PocketHealth enables healthcare organizations to seamlessly share records and surface clinical insights, while eliminating network image-sharing dependencies to create efficiencies, reduce costs, and keep patients at the center of their healthcare journey. 

PocketHealth maintains strict patient privacy, never sharing patient health data with third parties or using it for AI training. PocketHealth adheres to HIPAA and SOC 2-compliant security protocols, ensuring patient information remains encrypted, private and accessible only with proper authorization. Trusted by over 800 hospitals and imaging centers across North America and used by more than 2 million patients, PocketHealth is transforming the way medical imaging is accessed and shared. 

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At RSNA 2024, PocketHealth hosted a panel discussion where radiology leaders shared strategies for tackling interoperability challenges, improving patient engagement and overcoming budget and staffing constraints.

Moderated by PocketHealth CEO Rishi Nayyar, the panel featured, 

• Stacie Barnard, Enterprise Imaging Informatics & Integrated Clinical Systems (URMC),
• Fernando Martín, Architecture, DevOps & AI technologies (WellSpan Health),
• Dr. Ram Chadalavada, Vice Chair Radiology – Informatics, Associate Professor Radiology and Surgery (UC Health).

Together, they explored how imaging departments can move beyond the limitations of legacy systems to achieve tangible results through:

• Seamless Enterprise Image Exchange: Automating workflows, enhancing collaboration with referring physicians and significantly reducing operational costs.
  
• Intelligent Patient Engagement: Improving follow-up compliance, reducing missed appointments and delivering personalized experiences that increase patient retention.

Watch the full session to hear firsthand how these experts are improving image exchange and patient care.

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At RSNA 2024, PocketHealth Co-Founder and CEO Rishi Nayyar explored the important role image exchange plays in delivering coordinated care. Disjointed legacy workflows and outdated processes delay treatment, frustrate care teams and leave ⅔ of patients feeling out of the loop on their own care.

Nayyar explained how PocketHealth bridges these gaps by connecting real-time image exchange with intelligent patient engagement. This enables care teams to act quickly and effectively while keeping patients informed, engaged and supported at every step.

Watch the full session to see how to advance smarter, connected care.

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