Healthcare providers spend much of their operational time on repetitive phone calls with insurers, call centers, and other organizations.
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HeyRevia uses a real-time voice agent with perception, planning, and control layers to handle calls and let staff take over when needed.
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Healthcare deployment requires strict data retention, client isolation, compliant vendors, and ongoing attention to security and privacy.
Summary
Shaun describes the administrative phone work that supports healthcare, including insurance verification, prior authorizations, credentialing, referrals, and claims. Providers often rely on call centers because there is no better connection between the organizations involved. HeyRevia builds an AI call center that listens to live audio, understands IVR menus and hold music, plans the next steps, and negotiates with human representatives. Its system can pause processing while a call is on hold, then resume when someone answers. Staff can supervise several calls and take control of any one of them. Shaun says the system is evaluated against human performance and reports better results in some scenarios. He is also direct about healthcare constraints. The company hosts models itself, keeps client data separate, uses retention policies, checks vendor compliance, and maintains security updates. HeyRevia currently works on top of EHR systems rather than integrating with them directly.
Healthcare administration depends on repetitive phone work
Shaun says more than 30% of healthcare operations run through phone calls. Patients may call about appointments, while providers call insurers about credentialing, network access, denied claims, prior authorizations, referrals, and related issues. These calls repeat throughout the day and often require organizations to communicate through separate call centers. He argues that the phone remains the basic connection between clinics, professional service providers, and insurance companies, even when the work is routine.
Shaun explains that many voice agents connect telephone systems to streaming audio, speech recognition, a language model, and text-to-speech. The system must handle audio bytes, send complete text chunks to the model, and return generated audio. Small delays become noticeable because the pipeline processes audio continuously. He says systems can suffer when latency goes beyond 500 milliseconds, and a failure in the telephone or streaming layer can stop the call altogether.
Healthcare voice agents need tighter safeguards than ordinary call bots
Shaun says hallucinations are especially dangerous in healthcare. A wrong prescription volume or medication detail could harm someone. He also describes the difficulty of keeping a voice agent on task during a ten-minute conversation. If the system becomes confused, it may retry the same action or produce an unrelated result. These risks make it necessary to control the agent's behavior rather than rely on one large prompt.
HeyRevia models a call as perception, prediction, planning, and control
HeyRevia's agent listens to live calls and identifies whether it is hearing music, an IVR system, or a human. It predicts the right behavior, such as pressing a button or waiting. When the call is on hold, it pauses expensive model processing and waits silently. A planning layer lets the agent think ahead through the steps required to finish a task. A control layer provides guardrails that keep the conversation focused on its objective.
Shaun says a human can enter an active call, speak directly to the representative, and then return control to the AI. HeyRevia also offers a call center interface where a supervisor can watch 10 or 15 calls at the same time and intervene in an individual call. The company presents this as a way to keep accountability with staff while allowing the system to handle routine conversations.
The product can retry calls when it detects missing information
HeyRevia's work API lets customers submit call tasks and receive the resulting work. During a call, the system can recognize that a provider ID or NPI number is wrong, ask for the missing information, and retry the insurance call. Shaun says the agent can identify its own failure and continue after receiving the correction. Customers who want more direct supervision can use the call center UI instead.
Healthcare compliance extends to every vendor in the call path
Shaun says HeyRevia hosts the language models itself and applies retention policies so one client's data and training do not get shared with another provider or patient. He also says the company checks that speech-to-text, text-to-speech, and other service vendors meet the required compliance standards. The team monitors security issues and patches systems as standards and government requirements change.
Shaun says HeyRevia does not directly integrate with EHR systems yet. It operates as an AI call center on behalf of its customers, making the phone calls and returning the completed work. He describes the current product as a layer placed on top of existing systems, with customers still handling their own EHR workflows.
"You can actually jump into the call, take over the phone call, saying, "Okay, the AI, you just sit in the backseat. I'm going to take over the phone call.""10:56
Who should watch
You are building voice agents for regulated workflows and need to reason about latency, hallucinations, and human intervention.
Your healthcare operation still relies on staff or call centers for insurance, authorization, credentialing, or claims calls.
You need an example of how to evaluate an AI agent against human call performance while keeping customer data separated.
