2care vs Hyro, Assort Health and PolyAI

Hyro, Assort Health and PolyAI sit at the enterprise end of healthcare voice AI, and they are not the same product as each other: Hyro comes from the IT and contact-centre world, Assort Health is built around specialty protocols, and PolyAI is a contact-centre platform applied to healthcare. What they share, from the point of view of a practice comparing them with 2care, is that they are large, sales-led platforms aimed mostly at health systems, and that most of the engineering that decides how a call actually goes is not something they publish.

2care is the healthcare-native agent in this comparison, and it publishes its engineering because the engineering is the argument. This is a technical look at how a call is resolved, on the systems a practice actually runs, and what separates an agent that writes a real appointment into the record from one that routes a conversation.

The deepest difference is what happens at the end of a call. A contact-centre lineage, which two of the three share, is built to understand a caller and route or resolve within a conversational layer. A healthcare-native agent is built to finish the job in the system of record: read live availability, resolve the patient, apply the booking rules, and write the appointment back.

2care writes back in real time across 95 or more systems, including Epic, athenahealth, eClinicalWorks, NextGen, Cliniko and the rest, plus any HL7 FHIR R4 endpoint. The write is a first-class appointment against the resolved patient record, validated by the practice system, logged and reversible, not a summary handed to staff to enter. Where the enterprise platforms integrate, they often integrate at the contact-centre and telephony layer, or through a specialty protocol engine; the question to ask any of them is whether a booking lands in your EHR, against the right chart, while the caller is still on the line, which is the thing a practice actually needs.

The distinction is not academic. An agent that resolves a conversation but hands the booking to a queue has moved the work, not finished it, and on a practice that difference is the whole point of automating the phone. Writing back in real time also closes the loop that a routed call leaves open: availability is read live so a slot offered genuinely exists, the write is confirmed to the caller only after the record accepts it, and there is no second system holding a booking that has to be reconciled against the chart in the morning. A contact-centre layer can be excellent at understanding a caller and still leave that last, decisive step, the one that puts a real appointment on the real schedule, for someone else to do.

Where they differ, metric by metric

Dimension	2care	Hyro	Assort	PolyAI
Voice pipeline	Native, in-house, 480 ms reply	Conversational AI, IT lineage	Specialty protocol engine	Contact-centre platform
Turn-taking	Dual-signal, adaptive	Standard	Standard	Standard
Concurrent calls	1,000+	Enterprise-tier	Enterprise-tier	Contact-centre scale
Languages	50+, multilingual agents	Multiple	37	45+
Real-time EHR write-back	95+ systems, FHIR R4	Via integrations	20+ EHR/PMS	Telephony, contact centre
Patient matching	Scores, escalates ties	Standard	Protocol-based	Standard
Clinical escalation	3 to 4 sec SLA	Configurable	Via protocols	Call routing
Delivery model	Cloud-native, 99.9% uptime	Enterprise SLA	Enterprise SLA	Enterprise SLA
Compliance	HIPAA, GDPR, DPDP, BAA	HIPAA, enterprise	HIPAA	HIPAA, GDPR
Built around	The healthcare call	Enterprise IT	Specialty groups	Contact centres

Competitor figures are estimated from each vendor's public materials; 2care figures are our own.

Two things stand out in that table. On the metrics that decide a hard call, latency, turn-taking, escalation, write-back, 2care leads every row, because a healthcare-native pipeline is tuned end to end for exactly those. And these are capable enterprise products with real customers; the point is not that they cannot answer a phone, it is that they are built for enterprise breadth, while 2care is engineered around the healthcare call itself.

The native voice pipeline, in detail

Because the enterprise platforms do not publish their pipelines, the fair thing is to publish ours in full. 2care runs a native voice pipeline built in-house, not a wrapper over third-party voice services. Streaming speech recognition returns a usable partial transcript in roughly 120 milliseconds; an intent layer resolves the reason, provider, urgency and identity while the caller is still speaking; the model's first token arrives in around 180 milliseconds from a warm pool; and native text-to-speech begins audio in about another 120, for a total reply near 480 milliseconds, ninety-fifth percentile under 700 and ninety-ninth under 1,100.

Turn-taking uses dual-signal endpointing, the line going quiet and the sentence reading as complete, with an adaptive silence window around 550 milliseconds that widens for hesitant or distressed callers, and a barge-in that yields within about 200 milliseconds. Under load, the pipeline fails over between redundant native model instances before a caller hears a gap, so peak behaves like quiet. Owning every stage is what makes each of those numbers something we set rather than something we watch, which is the whole practical meaning of native, and it is exactly the layer a wrapper over external services cannot control.

Matching, escalation and the write

Three mechanisms decide the hard calls, and they are the same on every system 2care connects to. Patient matching generates candidate records, scores them on phonetic name similarity, date of birth and number, and requires both a confidence threshold and a wide margin to the second candidate; a close call is escalated to a person rather than written under a guess, so a chart is not duplicated. Clinical escalation runs through an Escalation Engine with real targets: routine resolved on the line, an emergency to a person in about three seconds, a clinical question to a nurse queue in about four, each carrying the transcript and the resolved patient, and every escalation records the trigger that raised it so the boundary is auditable. The write is idempotent and waits for the practice system to accept before a confirmation is spoken, so a retry never double-books and nothing false is ever promised. See the flow on the platform.

None of these three mechanisms is exotic, and that is the point: they are the ordinary, unglamorous engineering that a healthcare voice agent has to get right, and the reason to publish them is that they are exactly what a happy-path demo hides. A protocol engine or a contact-centre platform may well have its own answers to matching and escalation, but a practice cannot evaluate what it cannot see, and being able to read how the returning patient is resolved and how the clinical call is routed, before signing anything, is itself a difference worth weighing between an agent that puts its engineering on the page and one that keeps it behind a sales process.

Compliance a practice can read

A booking that transcribes a call, resolves a patient and writes to an EHR is creating and maintaining protected health information, which under HHS guidance makes the vendor a business associate, not a conduit. 2care signs a BAA, encrypts patient data with AES-256 at rest and TLS in transit, never trains shared models on it, and covers UK and EU deployments under GDPR and Indian ones under DPDP with data held in region. For a practice, being able to read exactly what a vendor signs and where data lives, on a page rather than through a procurement cycle, is itself part of the comparison. What 2care commits to is on the compliance page.

Where 2care is right for a practice

An enterprise platform can be the right choice for a large health system that wants a contact-centre-scale deployment, already runs the procurement to evaluate one, and needs the specific things those platforms lead with. Not every buyer is a practice, and where the buyer is an enterprise IT function, the enterprise tools belong in the evaluation.

2care is right for the buyer these three reach least well: a practice or group that wants an agent purpose-built around the healthcare call, writing back into the EHR it already runs, engineered visibly for the hard calls, and accessible without an enterprise procurement. It is right when the failure paths matter, the busy line that must not give a busy signal, the returning patient who must not duplicate, the clinical call that must reach a person in seconds, the write that must land in the record, and when a practice wants to read the engineering rather than take it on trust. The more a buyer values those, the more clearly 2care is the agent built for them.

Frequently asked questions

How is 2care different from an enterprise platform like these?

It is healthcare-native and built around resolving the call into the EHR, and it publishes the engineering that decides a hard call: the native pipeline, the endpointing, the matching, the escalation SLAs, the real-time write-back across 95 or more systems. The enterprise platforms are largely contact-centre or protocol lineages aimed at health systems, with those mechanisms behind a sales process.

Does 2care write back into our EHR in real time?

Yes, into 95 or more systems plus any FHIR R4 endpoint, as a first-class appointment against the resolved patient, validated by the practice system, logged and reversible. The confirmation is spoken only after the write is accepted, so nothing is promised that did not land.

What decides a hard call, technically?

The pipeline latency, the endpointing, the matching and the escalation. 2care replies in about 480 milliseconds, does not cut off a hesitant caller, escalates an ambiguous patient rather than guessing, and routes a clinical call to a person in seconds with SLAs and context. Those are the layers a happy-path demo never exercises.

Is 2care only for small practices?

No. It scales to 1000 or more concurrent calls at 99.9 per cent uptime, so it fits a busy multi-site group as well as a single practice. The difference from the enterprise platforms is that it is accessible to a single practice too, without an enterprise procurement.

How does its compliance compare?

2care publishes it: a signed BAA, AES-256 at rest, TLS in transit, no training on patient data, and GDPR and DPDP coverage with data held in region. Being able to read that on a page, rather than extract it during a sales cycle, is part of what a practice is comparing.

What to test them on

Do not judge any of these on a scripted demo, because all of them pass that. Test them on a booking that has to land in your EHR against the right chart, a hesitant caller, an ambiguous patient record, and a clinical call that must reach a person in seconds. That is where a healthcare-native, visibly engineered agent separates from a contact-centre one.

Hear 2care resolve exactly those calls into your own system on a live demo when you book a demo, or see the systems it writes back to on the integrations page.