Company profile · 4 min read
Elite: a per-resolved-interaction AI front office for healthcare
Elite uses AI agents for healthcare calls, scheduling, referrals, triage and follow-up inside existing EHR and phone systems.
Cofounder of Lazyweb (a16z Speedrun). Previously grew subscriptions and built native ads at Duolingo. Writes First1000 (90,000+ subscribers).
Published · Updated
Elite is an AI front office for healthcare practices that want missed calls, scheduling and referral work handled inside the systems they already use. The buyer fit is a practice with enough phone volume to pull staff away from patients, but enough routine work to define clear escalation rules.
What it does
The current Elite site says its voice, SMS and web agents answer calls, schedule and reschedule visits, route triage, handle referrals, follow up on refills, check eligibility and write to existing EHRs. It lists support for 18 specialties and more than 19 EHRs, including Epic, athenahealth, eClinicalWorks and ModMed. The site says pricing is per resolved interaction rather than per seat or minute, with a tailored quote.
Elite’s workflow is not limited to booking. Its public examples show rule-aware appointment matching, referral extraction, follow-up campaigns and escalation of complex questions to a human. Those examples are demonstrations and company claims, not an independent clinical-safety or patient-outcome evaluation. The site also says patient data is encrypted in transit and at rest, stored in the US, not used to train models, logged for audit and covered by a BAA before live patient data is used; validate those claims in a healthcare security review.
Why I’d look closer
The founder background fits the go-to-market challenge. The YC profile identifies Raj Jagiasi as having led GTM at Deel and Vihaan Jagiasi as an engineer at Cadastral before its acquisition by Legora. Their public product framing is specific about the front-office job: answer the call, apply the practice’s rulebook and leave the complex moment to staff.
The advantage is integration without a rip-and-replace project. The tradeoff is that healthcare calls mix scheduling with symptoms, medications, insurance and urgent situations. A polished demo does not establish safe triage, correct EHR writes or reliable behavior across every specialty.
What I’d ask
Which calls can be resolved without a human, and which are always escalated? How are emergency symptoms, medication requests, insurance uncertainty and identity verification handled? Can staff review every write-back and outbound message? What exactly does the per-resolved-interaction fee include, and how are failed or duplicate interactions counted?
My editorial take
Shortlist Elite if unanswered calls and referral follow-up are the measurable bottleneck. Start with scheduling and one specialty, keep clinical and billing decisions behind explicit rules and staff review, and verify EHR write-backs with controlled records before live deployment. The product’s value is operational continuity; its risk is pretending the front desk is only a calendar.
Quick facts
| Field | Sourced detail |
|---|---|
| Product | AI voice, SMS and web front office for healthcare practices |
| Buyer | Medical practices and healthcare operators |
| Integrations named | Epic, athenahealth, eClinicalWorks, ModMed and other EHRs |
| Pricing | Per resolved interaction; tailored quote, no public amount |
| Main question | Can routine volume be automated while triage and EHR changes stay safe and reviewable? |
Sources checked
| Source | Checked |
|---|---|
| YC company profile | 2026-09-19 |
| Elite homepage | 2026-09-19 |
Cohort context
Elite is listed in Summer 2026. In our 2026-09-18 directory snapshot, 22 of 232 listed companies in that cohort have YC’s primary industry label Healthcare (9.5%). This is a current-directory comparison, not an original intake count or a performance ranking. Nine-cohort dataset.
Public website snapshot
Observed 2026-09-19T16:18:48.066Z in raw homepage HTML. This records visible metadata and advertised links, not agent execution or product quality.
| Signal | Homepage observation |
|---|---|
| Product description metadata | Observed |
| Canonical link | Observed |
| H1 or H2 heading | Observed |
| Typed structured data | Observed |
| Docs/developer link | Not observed in this response |
| Pricing link | Not observed in this response |
| llms.txt link | Not observed in this response |
| Markdown alternate | Not observed in this response |
Public observations · Collection method. Missing links here do not establish that a capability or file is absent elsewhere.
About the author
Cofounder of Lazyweb (a16z Speedrun). Previously grew subscriptions and built native ads at Duolingo. Writes First1000 (90,000+ subscribers).
I cofound Lazyweb and publish Mudpie. This is an owner-written publication, not an independent testing organization. Research notes distinguish observations, sourced reporting and editorial judgment.
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