Hello Patient

Conversational agents are the product, and the company is candid about where the intelligence comes from. It states it does not build foundational or voice AI models but takes existing models and fine tunes them for healthcare practices and front office workflows, and describes rolling out a multi agent architecture to handle complex workflows reliably. That is an honest architectural disclosure most vendors avoid, and it does not diminish centrality: without the agents there is no product, only a phone line.

This is among the more autonomous deployments in the index: agents answer calls, book appointments, run intake, answer insurance questions, take refill requests, and handle billing outreach, with the company targeting a 100 percent answer rate and reporting practices moving from 20 to 30 percent of calls unanswered down to zero. The tasks are administrative rather than clinical, which contains the risk. What is not published is the escalation path when a patient raises a clinical concern mid conversation, or the confidence threshold at which a human is brought in, and for a system running triage adjacent intake that boundary is the thing a buyer should nail down.

Unusually forthcoming for this category. The company states plainly that it builds on existing foundational and voice AI rather than its own models, fine tuning for healthcare front office use, and that it has been fully generative and conversational from the start rather than layering AI onto scripted flows. Its voice infrastructure partner is publicly named. What is not published is which model providers sit underneath, evaluation methodology, or containment and accuracy measurement.

Operational metrics are specific but vendor reported and early. The company reports powering more than 100,000 phone calls and 300,000 patient conversations within roughly its first year, around 20 percent more appointments booked, and 25 to 30 percent conversion when reaching out to referral patients to get them scheduled. Named customers span med spa, behavioral health, and outpatient groups. The company was founded in 2024, so there is no longitudinal evidence, and no independent evaluation of conversation quality, error rate, or patient experience was located.

The company states HIPAA compliance and SOC 2 Type 2 certification directly, and the surface is real: agents handle inbound and outbound conversations that necessarily involve identifiable patient information, insurance details, and clinical context around refills and follow up. Stating both commitments plainly on the main site, rather than behind a sales conversation, is better practice than most vendors in this category. No disclosure was located on call recording retention or whether conversations inform model tuning.

HIPAA compliance is stated publicly and prominently alongside SOC 2 Type 2. No explicit business associate agreement commitment language was located, which is the element that would move this to an A given the agents process protected health information in every conversation they handle.

SOC 2 Type 2 is stated explicitly, and the type is specified, which matters because Type 2 tests operating effectiveness over a period rather than control design at a point in time. Naming the type rather than saying SOC 2 generically is a small but meaningful precision. No trust center or downloadable attestation was located.

No FDA pathway applies. The agents handle scheduling, intake, insurance, and billing communication rather than clinical assessment. The regulatory surface that does apply is telephony and messaging consent regulation, including TCPA obligations on outbound automated contact, which is a live consideration for a platform doing recall and reactivation outreach at volume, and no public position on that was located.

No governance framework or bias evaluation was located. The salient question for voice agents is performance across accents, dialects, speech impairments, and non English languages, since a system that answers every call but understands some callers less well shifts access rather than expanding it. The company offers multiple languages and configurable voice characteristics, but publishes no comparative performance data.

Integration is the precondition for the product working, since booking an appointment requires writing to the schedule. The company states it integrates with the EHR, practice management, and CRM systems healthcare organizations already run, with API integration into those systems described as the delivery mechanism. No specific named EHR integrations, certifications, or standards support were located, so breadth is asserted rather than enumerated.

No hosting, tenancy, or data residency disclosure was located. The platform is cloud delivered with a named third party voice infrastructure provider carrying the telephony layer, which introduces a second party into the data path that a buyer should account for.

No published pricing. The company positions the economics as handling more conversations without adding staff, an explicit substitution for call center headcount, which frames the comparison a buyer should make but discloses nothing about cost, per minute or per conversation basis, or minimum commitment.

Broad across outpatient settings and explicitly multi specialty, with named or demonstrated use spanning urgent care, primary care, dermatology, orthopedics, ENT, dentistry, mental health, med spa, and veterinary practice. Target buyers are multi location medical groups and health systems as well as digital health companies. Inpatient and acute care are outside scope, and the veterinary inclusion is worth noting as a signal that the platform is built around conversation patterns rather than clinical domain.