Product walk-through — the real screens, every user, vs the incumbent
One encounter, every user — watch it beat the incumbent
This is the actual product, embedded live. Start at the minute-level self-scheduler, then click through a real primary-care encounter from each person's seat — patient, front desk, provider, RCM/coding, and billing. At every step you can open the live screen, and a callout shows how it beats the rules-based incumbent.
Start here: the minute-level self-scheduler
Most schedulers are calendar grids. REV treats the practice as a graph of resources (providers, rooms, MAs, equipment) and solves the whole day at one-minute resolution, re-optimizing live when reality intrudes.1 Patients self-book from the portal — filtered by plan network, with an eligibility check fired automatically.
- Resource-graph, not a calendar grid. The practice is modeled as providers, rooms, MAs and equipment; the solver books across all of them atomically, so a slot is only offered if the practice can actually run it.1
- One-minute resolution. The whole day is solved at minute granularity (<250 ms search) — not fixed 15-/30-minute blocks — so it packs tighter and lifts provider/room utilization ~20%.2
- Live re-optimization. A no-show or an over-running visit re-floats every downstream stage in under two seconds, keeping each patient inside their wait-time SLA.1
- Eligibility at booking. A 270/271 fires the moment a patient self-books, so coverage problems are fixed before the visit — a direct first-pass-clean-claim driver.2
Minute-resolution solver
Returns the best feasible windows in <250 ms and books atomically across provider, room, MA and equipment — a calendar grid would double-book the room.1
Patient self-serve
Established patients book at 9 pm with no phone call; eligibility (270/271) fires automatically and a cost estimate shows at booking.1
Walk-in absorption + waitlist auto-fill
A no-show is detected at the 10-minute mark and SMS-offered to the top waitlist match; walk-ins slot into the smallest window that keeps every booked patient inside their wait-time SLA.1
~20% scheduling efficiency lift
Tighter packing and live re-optimization raise provider/room utilization — a measured contributor to REV's collections lift.2
The encounter, seat by seat
Pick a user. Each step is the live screen, with how it beats the incumbent.
Self-schedule the visit
PatientThe patient books from the portal in under a minute — network-filtered, eligibility checked, cost estimated up front.
▲ The live self-scheduler is embedded at the top of this page — jump to it
Incumbent portals show a static calendar grid that ignores room and MA capacity. REV solves the whole resource graph at minute resolution, so the slot a patient self-books is one the practice can actually run.1
Digital check-in & intake
PatientForms, history and consents are completed on the patient's phone before arrival — no clipboard, no re-keying.
Paper/standalone intake means staff re-key data and errors leak into the claim. REV's intake writes straight into the chart and the claim scaffold — one source, captured once.
Portal timeline & messages
PatientAfter the visit the patient sees results, the plan, and secure messages on one timeline.
Incumbent patient portals are bolt-ons with separate logins and lagged data. REV's timeline is the same record the clinician uses — live, not a nightly copy.
Check-in
Front deskArrivals are confirmed in a tap; anything missing from digital intake is surfaced, not hunted for.
No swivel-chair between a scheduler, an eligibility tool and the EMR — it's one screen, one record.
Eligibility & benefits
Front deskThe 270/271 already fired at booking; the desk sees coverage, copay and any problem before the patient sits down.
Rules-based shops check eligibility at the desk (or discover the problem on the denial). REV checks at booking, so coverage issues are fixed before the visit — a direct first-pass-clean-claim driver.2
Rooming
Front desk / MAThe solver routes the patient to a free room and MA, keeping everyone inside the wait-time SLA even when a visit runs long.
On a calendar grid, one 9:30 overrun pushes every afternoon patient late. REV re-floats downstream stages in under two seconds and absorbs the slip.1
Ambient AI scribe
ProviderThe visit is documented as it happens — the note is finished before the provider leaves the room.
Incumbents transcribe a free-text note and a coder re-reads it later. REV's scribe is structure-first: it works the encounter as a set of questions that resolve to discrete, coded fields, so the same visit produces the same correct codes every time. Documentation and coding are one step, not two.3
Coding at the point of care
ProviderThe encounter is coded to documentation-supported specificity in the room — not under-coded for safety and reworked later.
Rules-based coding is static and never improves. REV's model learns from every encounter, every insurance denial and every coding error, lifting accurate capture by ~15% on the ML path while staying documentation-supported.2
Clean claim, first pass
RCMBecause the visit was captured and coded correctly live, the claim goes out clean — ~98% on first pass.
Denials prevented, not chased
RCMThe system flags what would deny before the patient is seen — coverage, auth, coding — so most denials never happen.
Rules-based RCM catches denials after the payer says no. REV shifts left and prevents them — the difference between an AI model and a static rules engine.4
Automated appeals
RCMWhen a denial does land, the appeal packet is generated automatically with the supporting documentation attached.
Appeals at incumbents are manual letters from a billing shop. REV drafts and assembles them — labor the incumbent pays for, automated away.4
ERA auto-posting
BillingRemits post automatically and reconcile against expected; exceptions are the only thing a human touches.
Manual posting is a standing cost line at incumbents. REV automates it, so billing headcount doesn't scale with claim volume.4
AR worked continuously
Billing / ARAging is worked by the system in the background, prioritizing what will collect — not a monthly human sweep.
Incumbents work AR in a monthly, oldest-first human sweep. REV works it continuously and prioritized by what will actually collect — so cash lands faster and less ages into write-off, without adding billers as volume grows.4
Patient payments
Billing / PatientEstimates shown at booking become a simple digital bill — fewer statements, faster cash.
REV's unique building blocks — what the incumbents don't have
Beyond the encounter above, three more artifacts only REV produces — each shown live, each with why we win. (The structured encounter itself is the Provider screen you already saw, so we don't re-show it — just the point below.)
Structured encounters
REV-only · shown in the Provider tabEvery visit is captured as structured data, not a free-text blob — Reason → Chart → SOAP → Plan & Coding → Billing as discrete, queryable fields. You saw it live above: open the Provider → Ambient AI scribe screen ↗
Legacy EMRs store the note as free text and re-key it for coding and billing. REV's encounter is one structured record that drives the note, the codes and the claim at once — no re-entry, no downstream drift, and every field is queryable for analytics and RCM. That structure is why a single AI pass can produce the note, the code and a clean claim.3
The patient record
REV-onlyOne longitudinal record per patient — encounter notes, vitals & trends, labs and imaging on a single timeline — the same record the clinician, the patient and RCM all see.
Incumbents fragment the chart across modules and bolt-on portals. REV keeps one longitudinal record across every encounter, specialty and document — clinician, patient and RCM all read the same live data, so nothing is re-keyed or reconciled between systems.
Encounter receipts & PDFs
REV-onlyAfter every visit REV generates the patient-facing artifacts automatically — treatment / care plan, after-visit summary, and an itemized bill & benefits — each viewable and downloadable as a clean PDF.
These are produced from the structured encounter, so they're correct and instant — not assembled by hand or pulled from a separate billing system.
RCM tasks
REV-onlyThe RCM team works from a single prioritized queue — triage, claims, denials, AR and appeals — with each task tied to the patient and encounter that created it.
Incumbents run RCM in separate tools disconnected from the chart. REV's queue is small because claims go out clean, and every task links straight back to the encounter that created it — one system to resolve an exception, not a bolt-on worklist and a swivel-chair.4
Sources
- Minute-level resource-graph scheduling — constraint solver at one-minute resolution (<250 ms search), atomic multi-resource booking, walk-in absorption, waitlist auto-fill, patient self-scheduling with auto-eligibility. REV product spec: Scheduling — resource-graph, minute-level.
- Efficiency & positioning facts — scheduling efficiency ~20%, ML/coding efficiency ~15%, ~27.5% efficiency vs ECW, ~98% first-pass clean claims, nearest-competitor all-in ~$1,000/mo. Source: investor-portal facts.json (positioning), derived from the proforma export + positioning source.
- Ambient AI scribe / "note done before you leave the room" — documentation and coding as a single step. REV product: clinical documentation; narrative in EMR/RCM deep dive.
- AI-native RCM vs rules-based incumbents — denials prevented pre-visit, automated appeals, continuous AR, cost-to-serve toward ~1.3% of collections vs a labor-heavy incumbent workforce. See margin defense and coding analysis.
- All-in pricing & TCO vs incumbent — $595/provider/mo incl. AI + 4.9% of collections; head-to-head total cost: EMR compare.
Live product demo. The embedded screens are the REV.health demo build; figures shown inside individual demo screens are illustrative. Efficiency and clean-claim percentages are positioning assumptions from the model export, not audited results.
EMR/RCM deep dive · EMR compare · Margin defense · Portal home