AI employees for speech therapy clinics
The back-office leak grows at every location you can't see into.
Authorizations expire before anyone notices. Intake packets go out and only half come back. Denials pile up faster than one biller can work them. The same work falls through the same seams at every site.
Relay builds custom AI employees for multi-location speech therapy clinics. They work on top of the EHR your group already runs, whether that is WebPT, Raintree, Fusion by Ensora, or another system. They handle high-volume back-office work across every location and hand each finalized action to a staff member.
The model is healthcare-specific and human-in-the-loop, billed as a recurring monthly fee. Relay is not an EHR. At Sensory Speech and Occupational Therapy, a multi-location pediatric speech and OT group, two AI employees built on top of their existing stack, and the group saw 100% claim accuracy, staff 33% more productive, and claim denials down 12%.
What leaks at one location multiplies across all of them.
One location can paper over a broken seam with a heroic coordinator. Three, five, or ten locations cannot. The authorization spreadsheet lives on one site's desktop. Denial patterns differ by payer per site. Reporting gets reconciled by hand at month-end.
This is not a software install. It is a cross-location operating layer your current stack does not include. Relay is custom-built for this specific complexity, not a generic AI tool bolted on top.
AI employees run the cross-location back office on top of the systems you already run (WebPT, Raintree, Fusion, SimplePractice), and a staff member finalizes every action. You keep control while the AI does the watching and the drafting. This covers credentialing-to-billing visibility, multi-site productivity, and the shadow-spreadsheet work your current stack leaves to your coordinators.
Where your speech therapy clinic is leaking revenue.
Five places the back office leaks at every location. Open the ones that sound like your clinic.
Families with young children return half the forms, forget a signature, or photograph only the front of the insurance card. An AI employee watches the intake queue for each family, flags exactly what is missing, and sends a follow-up asking only for the missing item rather than the whole packet again. When the packet is complete, it routes to the coordinator to verify in one action.
Incomplete intake delays the eligibility check. That delays the prior auth. That pushes the first billable visit back by weeks. The AI also pre-validates: it cross-checks submitted insurance IDs against the eligibility layer before the first appointment is booked. Coverage gaps surface before the visit instead of after the claim. The human confirms; the AI chases.
Across two or more locations, the coordinator is chasing every family at every site at once. An AI employee consolidates the queue and delivers one sorted action list per location, not a pile of follow-up calls. Pediatric intake requires guardian coordination, developmental and case-history forms, HIPAA authorizations, a physician referral, and a signed plan of care. A plan-of-care signature is required for Medicare Part B SLP billing; an unsigned plan of care is a direct denial and audit risk.
The first billable visit happens on time instead of sitting in a missing-forms queue for weeks.
An AI employee runs batch eligibility checks against the next-day and next-week schedule. It compares benefits to the expected CPT codes and delivers a pre-sorted action list to the billing coordinator before the visits happen. On authorizations, it tracks units used versus authorized, the expiration date, and sessions scheduled against remaining units. It then drafts the re-auth packet from the existing clinical record for a staff member to review and submit. It catches underutilized hours before the period closes, not just expired ones.
Auth data lives in your EHR, but nothing reliably alerts you before authorized units run out or the end date passes. Eligibility has to be re-run because coverage changes month to month. Both are per-patient manual queues that become a part-time job across a multi-location clinic running dozens of visits a day. When a check gets skipped, claims go out on terminated policies and come back as hard denials, often past the timely-filing window.
Payer prior-auth rules for SLP change frequently by plan and state. A layer that tracks rule changes by payer beats relying on staff memory. The platform surfaces the signal; the AI prepares the action; a staff member finalizes.
Expired-auth denials stop landing in the queue after the window to fix them has already closed.
An AI employee works both ends of this. Before submission it scrubs each claim. It confirms every session has an active auth, the correct SLP CPT code, the required modifier, and a signed plan of care. Failures route to the coordinator with a specific reason. After a denial lands, it reads the reason code, retrieves the session note, auth, and EOB, drafts the appeal or corrected claim, and prioritizes the queue by appeal deadline so the expiring ones get worked first.
At a multi-location clinic, the billing coordinator is often one person touching dozens of claims a day. Front-end errors that look small, such as a wrong modifier, a missing auth number, or a CPT code the note does not support, pass the clearinghouse scrubber and fail weeks later at the payer. A denial not appealed before the window closes is revenue permanently written off.
The claim scrub checks SLP CPT codes (92507, 92521-92524, and related codes), confirms the GN modifier is present on Medicare Part B claims, applies the KX modifier when the threshold is exceeded, and confirms a signed plan of care is on file before the claim goes out. Clean claims go to the clearinghouse, flagged claims get fixed first, and worked denials get prepped for one-click resubmit. A staff member reviews, approves, and submits every one; Relay never submits autonomously.
Denials get worked before the appeal window closes, not after.
An AI employee watches the schedule in real time. When a cancellation hits, it texts the waitlist for that therapist's specialty and time block and surfaces the first confirmed replacement for the front desk to approve, with no manual phone round needed.
In pediatric speech therapy, a no-show is rarely just a no-show. The next family on the waitlist needs parent coordination and often insurance re-verification before they can take the slot. Across a full roster of therapists per location, unfilled slots add up to lost revenue every week.
The AI also makes booking auth-aware. Before a reminder or fill goes out, it checks that the patient's authorization covers the upcoming visit type and that coverage is still active. It flags any pre-visit action so the front desk handles it right then, not at check-in. The same function that chases the waitlist also checks coverage, so the slot refills clean instead of becoming a denial later. A staff member confirms every send.
Cancelled slots get refilled the same hour instead of sitting dead until the next day.
An AI employee tracks each provider's credentialing matrix across providers, locations, and payers. It monitors CAQH attestation expiration, state license renewal, and payer enrollment status. It sends staged alerts ahead of each deadline, pre-fills the re-attestation checklist from data on file, and blocks claims from going out to payers where enrollment is not yet confirmed.
A new SLP who is fully credentialed but not yet enrolled with a specific payer generates denials the moment that payer is billed. Sessions rendered during a credentialing lapse are often unrecoverable. CAQH ProView re-attestation is required every 120 days, and staff routinely miss it because the deadline is not surfaced in the EHR or billing system. A coordinator reviews and submits.
Premature claims stop going out before enrollment is confirmed.
Every denial you don't work in time is permanent.
In 30 minutes we'll show you exactly where your speech therapy group is leaking revenue. Built by a former compliance officer at a multi-location pediatric therapy group.
See where you're leakingWhy AI employees, not a generic tool or another hire.
Solution-aware buyers weigh a few options. Here is how they compare at a category level.
| Approach | What it means in practice | The tradeoff |
|---|---|---|
| Generic AI point tool | Sends reminders and chases documents without clinical context | Does not know SLP CPT codes, GN/KX modifiers, or payer-specific PA rules, so it creates new compliance exposure |
| Hiring more administrative staff | Adds headcount that scales linearly with location count | Does not change the manual process underneath; the denial queue grows at the same rate with two billers as with one |
| Rip-and-replace EHR | 12-to-18-month data migration and clinical workflow disruption | No assurance the new platform closes the auth and billing gaps the last one had |
| AI employee layer on top of your stack | Works on WebPT, Raintree, Fusion, SimplePractice, or CentralReach today | Healthcare-specific, human-in-the-loop, no rip-and-replace, a staff member finalizes every action |
Generic AI point tool
What it means in practice
Sends reminders and chases documents without clinical context
The tradeoff
Does not know SLP CPT codes, GN/KX modifiers, or payer-specific PA rules, so it creates new compliance exposure
Hiring more administrative staff
What it means in practice
Adds headcount that scales linearly with location count
The tradeoff
Does not change the manual process underneath; the denial queue grows at the same rate with two billers as with one
Rip-and-replace EHR
What it means in practice
12-to-18-month data migration and clinical workflow disruption
The tradeoff
No assurance the new platform closes the auth and billing gaps the last one had
AI employee layer on top of your stack
What it means in practice
Works on WebPT, Raintree, Fusion, SimplePractice, or CentralReach today
The tradeoff
Healthcare-specific, human-in-the-loop, no rip-and-replace, a staff member finalizes every action
Relay was founded by a former compliance officer at a multi-location speech and occupational therapy group. The authorization and billing patterns built into the AI employees came from that operational experience, not from generic healthcare AI training.
Works on top of WebPT, Raintree, Fusion, SimplePractice, and the rest of your stack.
Relay is not an EHR and does not replace one. AI employees layer on top of the platform you already run, closing the prior-auth, denial, intake, and scheduling gaps the platform leaves to your staff, never as a rip-and-replace.
WebPT tracks authorizations and runs eligibility but does not proactively alert when visit counts approach the authorized cap, and the eligibility-to-auth handoff between staff is where front-end denials originate. Relay reads WebPT's auth and schedule data, flags caps before the visit, and prepares the re-auth and clean claim for staff to review and submit. Integration surface: HL7 v2 (ADT inbound, BAR/DFT outbound billing, MDM/ORU clinical docs), 60-plus partner integrations. No public REST/FHIR; work through WebPT's partner program or middleware.
Raintree requires authorizations to be updated across multiple locations and has limited alerting for missing critical chart data. Relay reconciles auth status across sites and surfaces the missing-data flags Raintree does not. Integration surface: modern developer portal with a flexible API, active GitHub presence, Kno2 interoperability, pVerify/Waystar/Infinx partners. Confirm current API scope with Raintree's partnership team.
Fusion surfaces expiring authorizations in reports but does not auto-initiate renewals or alert front-desk staff in time, and clients cannot self-reschedule (every change routes through admin). Relay reads the report data, drives the renewal draft, and chases reschedules. Integration surface: no public REST/HL7/FHIR for third parties; integration via negotiated data feed or structured export.
Prior auth in SimplePractice is entirely manual (auth numbers hand-entered per chart, no expiration alerting), denial management is minimal, and intake is not deeply automated. Relay adds the alerting, denial triage, and intake chase on top. Integration surface: no formal public REST API, portal-first, CSV export; integration via negotiated partner arrangement or structured export.
Tebra auth tracking falls through the cracks, denials lack in-platform resolution guidance, and phones roll to voicemail at lunch and after hours. Relay tracks auths, drafts denial corrections, and handles overflow intake routing. Integration surface: legacy SOAP API plus a newer FHIR R4 REST endpoint (US Core, SMART on FHIR OAuth 2.0) and a Partner Marketplace.
Used by multidisciplinary groups running SLP alongside ABA, CentralReach documents six authorization failure modes itself, and OT/SLP workflows are second-class to its native ABA flows. Relay tracks the auth burn-down and works the SLP-specific seams on top. Integration surface: REST API (OAuth 2.0 client credentials, JWT) via the CR Preferred Partner Network (gated; apply for access).
ClinicSource explicitly states it does not offer a public API, has no prior auth automation, and no native eligibility verification. The primary integration surface is the CSClear clearinghouse (ClinicSource's own offering, powered by Availity) and structured CSV exports. Relay monitors the ERA feed from Claim.MD, categorizes denials by reason code, and routes corrected claims to the biller for approval and resubmission.
Relay uses these as data sources and pipes, not competitors. pVerify and Availity (270/271 eligibility and PA network) feed the eligibility and auth checks. Waystar, Office Ally, and Claim.MD feed the denial and ERA categorization. NexHealth, Weave, Klara, and Solutionreach are the communications channel; Relay adds the SLP-specific clinical context and auth-awareness on top. Updox and Doximity DocFax inbound faxes (referrals, PA approvals, denial letters) get classified, extracted, and routed; staff confirm.
How we build it.
We start from the problem you feel, then build the fix on the systems you already run. Discovery and your first working AI employee take 2 to 3 weeks. The full build runs 8 to 12 weeks.
Start with a free 30-minute call
A short call about where the work is piling up and what that is costing you while it stays manual. No commitment, and you leave knowing where you would start.
Discovery and your first AI employee (weeks 1 to 3)
A few working sessions with your team. We map your operation end to end, every workflow across your locations, and find where the money leaks and what closing it is worth. You do not walk away with just a document. By the end of discovery we have built your first working AI employee on top of the systems you already run, so you see it pay off in your real setup before the full build starts.
The full build (8 to 12 weeks, start to finish)
We build the rest of the AI employees you mapped and wire them across every location. Nothing goes out until your team approves it, so you stay in control the whole way. One pediatric therapy client had all seven locations live within 90 days.
Proof: Sensory Speech & Occupational Therapy.
Sensory Speech and Occupational Therapy is a multi-location pediatric speech and OT group. Relay built two AI employees on top of their existing EHR and Drive, with a staff member finalizing every action.
The intake AI employee runs the new-client lifecycle end to end: schedules clinic tours, gets ROIs signed, requests records from schools and prior speech and OT clinics, requests IEPs, sends medical orders to the child's PCP and follows up until signed, starts authorization renewals about a month out, and sends three-month progress reports and evaluations to PCPs for signature.
The internal auditing AI employee reviews every note nightly against the clinic's clinical requirements, confirms the billing code matches the note, and after billing finds and appeals denied claims (pulling from the EHR and Drive) and reconciles remittances against the EHR notes.
The group saw 100% claim accuracy, staff 33% more productive, claim denials down 12%, and faster documentation turnaround. These are the client's reported results, attributed to Sensory Speech & Occupational Therapy, and results vary by clinic.
AI employees for speech therapy clinics: frequently asked questions.
They run the high-volume back office across every location. That means chasing intake, verifying eligibility, tracking authorizations, scrubbing claims, working denials, filling cancellations, and watching credentialing deadlines. They work on top of the EHR you already run, and a staff member finalizes every action before it goes out.
No. Relay is not an EHR and replaces nothing in your clinical stack. AI employees layer on top of the platform you already run and close the gaps it leaves to your staff. There is no rip-and-replace and no data migration.
An AI employee monitors units used versus authorized, the expiration date, and sessions scheduled against remaining units in your EHR. It flags re-auths before the date passes and drafts the re-auth packet from the clinical record for a staff member to review and submit.
Yes, at two stages. Before submission, it prevents the front-end errors that cause most SLP denials: missing auth number, wrong modifier, a CPT code the note does not support, lapsed eligibility. After a denial lands, it drafts the appeal or corrected claim prioritized by deadline. A biller approves and submits every one.
Yes. The claim scrub checks that the SLP CPT code matches the session note, the GN modifier is present on Medicare Part B claims, the KX modifier is applied when the threshold is exceeded, and a signed plan of care is on file before the claim goes out.
When a slot cancels, the AI employee texts the waitlist for that therapist and time block and surfaces the first confirmed replacement for the front desk to approve. It also checks that the new patient's authorization covers the visit before the confirmation goes out.
No. Relay is human-in-the-loop by design. The AI does the watching, drafting, and preparation. A staff member reviews and finalizes every claim, appeal, note, and submission. The AI never signs and never submits autonomously.
Through the data paths that do exist. That includes the clearinghouse claim and ERA feed (Claim.MD for ClinicSource; Office Ally or CSV export for SimplePractice), structured exports, and the communications and intake tools in your stack. The integration surface differs by platform; Relay maps to whatever the platform actually exposes.
Yes. An AI employee tracks each provider's CAQH re-attestation, license renewals, and payer enrollment across every location and payer. It alerts before deadlines and blocks claims to payers where enrollment is not yet confirmed.
"AI agents" describes the technical building blocks. "AI employees" is how they show up to your clinic: scoped to a real role (intake, billing, scheduling) with a human finalizing the work. Same technology, framed by the job it does.
Yes. Relay operates as a Business Associate, signs a BAA as part of the engagement, and processes protected health information only within the agreed-upon scope of work. Every AI employee action is logged and auditable by your team.
The first two to three weeks are discovery: working sessions to map the operation and find the highest-value gaps. Builds run eight to twelve weeks. The model is a recurring monthly engagement, not a one-time installation.
It is a free intro call to find where your operation is leaking. We do a quick read on where revenue and staff hours are going, location by location and workflow by workflow. If it makes sense to go further, mapping the operation in depth happens in the first two to three weeks of the engagement, not on this call.
See where your speech therapy group is leaking.
The authorization that just expired. The intake packet still stuck in a family's inbox. The denial sitting in the queue past its appeal window. Those are the seams that multiply at every location you add. In 30 minutes we can show you exactly where your group is leaking, workflow by workflow and location by location. Relay was built by a former compliance officer at a multi-location speech and occupational therapy group. The workflows built into the AI employees came from that operational experience.