ComparePre-production

Everyone sells a segment. We operate the whole path.

An EMR captures the encounter, a clearinghouse translates the claim, an RCM tool chases the payer, a processor moves the money — each owns one hop. shteg.ai runs the whole track on one ledger.

This page compares how the systems are built, not how they perform — shteg.ai is not yet in production, and the incumbents named here have real, proven scale.

See the design contrasts Read the honesty note

Every statement about another company reflects only its own public positioning, stated factually and without disparagement.

How to read this page

Design and doctrine, stated factually — not a scoreboard.

The seams between segment vendors are where trust, money, and audit trails leak — so shteg.ai treats encounter-to-settled-money as one loop on one hash-chained ledger with a single deterministic gate. The right-hand columns below describe only how the field positions itself publicly.

Structural differences by construction

The shteg.ai approach vs. how the field generally works.

Six dimensions where shteg.ai is architecturally distinct. The right column describes only how the established field generally positions itself publicly — stated factually, without disparagement.

shteg.ai approachstructurally different by construction

How the field generally workspublic positioning, described factually

Deployment sovereignty: Cloud, Dedicated VPC (CMEK), or Sovereign K8s

shteg.ai approach

Available in three architectural deployment models: Enterprise Cloud (multi-tenant GCP), Enterprise Dedicated (single-tenant dedicated VPC, dedicated Postgres/K8s, Cloud KMS CMEK key control), and Enterprise Sovereign (open Helm chart for air-gapped on-premise Kubernetes, local Dex IdP SSO, MinIO S3 WORM storage, and local edge model inference). Data residency and root encryption keys remain strictly under customer jurisdiction.

How the field generally works

Established health IT and EMR platforms are overwhelmingly delivered as proprietary, multi-tenant black-box SaaS or legacy on-premise fat-client Windows servers. Customers have zero control over cloud encryption keys (CMEK), cannot run air-gapped without external telemetry, and are locked into vendor-controlled identity providers.

Owns the encounter→settlement loop on one ledger

shteg.ai approach

One system spans the clinical encounter through settled money, and every financial posting lands in a single hash-chained, write-once, append-only double-entry ledger with fork, orphan, and cycle detection. The audit trail is assembled as events happen rather than reconstructed afterward from fragments held by different vendors. Money is carried in conserving integer cents, never floating dollars.

How the field generally works

The field is generally composed of best-of-breed specialists that each own one segment — a specialty EMR/PM for the encounter and scheduling, a clearinghouse for claim routing, an RCM platform for follow-up, and a payments provider for money movement. Each vendor keeps its own records, and the end-to-end audit trail is stitched together across handoffs and reconciled after the fact.

Compliance lives inside the money path, not beside it

shteg.ai approach

PHI handling, Business Associate Agreements, and credentialing status are treated as design constraints that sit directly in the authorization path: where a required BAA or credential is not in place, the touching integration fails closed and money does not move. Compliance is a precondition of settlement rather than a downstream report.

How the field generally works

Payments, clearinghouse, and RCM vendors typically expose compliance as adjacent governance, reporting, and configuration layers — audit logs, access controls, and certifications maintained alongside the transaction flow. Correctness is generally enforced by rules engines and post-hoc reconciliation rather than by blocking the money instruction itself at authorization time.

Registered HIPAA clearinghouse identity (real Type-2 org NPI)

shteg.ai approach

shteg.ai is itself a registered HIPAA clearinghouse and therefore a covered entity, with its own Type-2 organizational NPI. That identity reshapes claim routing and compliance obligations from the inside — the clearinghouse role is the company’s own regulatory posture, framed to a covered-entity standard rather than to a general SaaS privacy posture.

How the field generally works

EMR, RCM, and payments vendors generally are not themselves clearinghouses; they connect to established clearinghouse networks (or are business associates) to reach payers. Dedicated clearinghouses do hold this role, but they typically operate as a routing and connectivity layer distinct from the EMR and the money-movement rails, so the clearinghouse identity and the settlement system belong to different parties.

Propose-never-dispose: agents propose, a gate disposes

shteg.ai approach

Automated and agentic components are constrained to propose changes; a deterministic gate — and, where appropriate, a human — disposes. The system is designed so that automation cannot unilaterally commit a state change or a money movement it has merely computed, keeping a reviewable boundary between suggestion and action.

How the field generally works

Modern RCM and automation platforms increasingly emphasize straight-through processing and AI that acts on claims, denials, and workflows autonomously to maximize throughput and reduce manual touches. The public value proposition is often the degree of automation and hands-off resolution, with human review positioned as an exception rather than the disposing step.

Fail-closed by default, behind a gate that is not swappable

shteg.ai approach

A deterministic six-condition settlement gate is the sole authorizer of every money instruction, with a kill-switch and a database-level halt sitting above it. When any condition is unmet, the correct behavior is to stop rather than press on and reconcile later. Vendors and integrations are deliberately swappable; the gate is not. Failing closed — unconfigured integrations return typed refusals and make zero network calls — is the default state, not the exception.

How the field generally works

Payment and RCM infrastructure is generally optimized for availability, throughput, and successful completion, with retries, queuing, and reconciliation workflows to recover from failures after they occur. Money movement typically proceeds through configurable rules and provider APIs, and the safeguards are framed as controls and monitoring around a system whose default posture is to complete the transaction.

Honest status posture: verified-green vs. gated

shteg.ai approach

shteg.ai publishes an honest register that separates what is tested in the current build (verified green) from what is genuinely gated on a named human or legal step — an AML program, a money-transmission legal opinion, FedNow certification. It states plainly that no real dollar has moved and no real PHI has flowed, and it describes controls as engineered rather than certified wherever certification is pending. The honest register is presented as the security posture, not a marketing afterthought.

How the field generally works

Established vendors market live, production capabilities backed by real customer traction, transaction volume, certifications, and case studies. Their public materials generally foreground proven scale and outcomes — appropriate for shipped, in-market products — rather than a line-by-line separation of what is code-complete from what is gated on an external legal or certification milestone.

The established field

How the field describes itself — and where shteg.ai differs.

Each entry reflects only that company’s own public positioning, described factually and without disparagement. There are no invented benchmarks, no head-to-head performance numbers, and no “we win” scorecards. The named incumbents are established, in-market products with real, proven scale; shteg.ai is not.

Specialty EMR + practice management

Company	Their public positioning	How shteg.ai differs (by design)
NextechOphthalmology / specialty EMR + PM	Specialty-specific EHR and practice management for ophthalmology, dermatology, plastic surgery and med spa, positioned as an all-in-one platform with patient engagement and revenue-cycle services.	Nextech centers the specialty clinical and practice-management workflow. shteg.ai is not a competing specialty EMR; it treats the encounter as the start of a single loop that continues through claim routing and settled money on one hash-chained ledger, and it is itself a registered clearinghouse rather than connecting out to one.
ModMed (Modernizing Medicine)Ophthalmology / specialty EMR + PM	Physician-built, specialty-specific EHR (EMA) with adaptive learning, practice management, analytics, and ModMed-branded RCM services across specialties including ophthalmology.	ModMed’s public strength is the specialty clinical experience plus optional RCM services layered on top. shteg.ai’s differentiator is not the clinical UI but the deterministic settlement gate and covered-entity clearinghouse identity that make compliance a precondition of money movement rather than a service alongside it.
CompulinkOphthalmology / specialty EMR + PM	All-in-one specialty EHR and practice management (Advantage) for ophthalmology, optometry, and other specialties, with integrated billing and RCM offerings.	Compulink bundles clinical, PM, and billing within one specialty suite. shteg.ai’s design point is what happens at the money boundary — a fail-closed, six-condition gate on a WORM ledger — and an audit trail assembled as events happen rather than reconstructed from separate modules.

Clearinghouse / health information network

Company	Their public positioning	How shteg.ai differs (by design)
AvailityClearinghouse / health information network	One of the largest real-time health information networks, connecting providers and payers for eligibility, claims, remittance, and prior authorization, with a widely used provider portal.	Availity operates as a connectivity and routing network between providers and payers. shteg.ai holds the clearinghouse role too, but folds it into a single system that also owns settlement and audit, rather than sitting as a routing layer that hands off to separate RCM and payments systems.
Optum / Change HealthcareClearinghouse / connectivity + RCM network	A very large clearinghouse, connectivity, and revenue-cycle network (part of Optum/UnitedHealth Group) spanning claims, eligibility, payments, and analytics across the industry.	Change/Optum offers enormous, proven scale across many separately consumable services. shteg.ai makes the opposite bet at pre-production scale: consolidate the loop onto one ledger with one non-swappable settlement gate, and be explicit that it is architecture and clearinghouse identity, not traction.
WaystarClearinghouse / cloud RCM platform	Cloud-based revenue-cycle and clearinghouse platform covering claims management, denials, payer connectivity, payments, and the patient financial experience.	Waystar’s public emphasis is end-to-end RCM performance and automation across the revenue cycle. shteg.ai frames the same territory around a deterministic gate that fails closed and a propose-never-dispose boundary, prioritizing auditability and stop-on-doubt over straight-through throughput.
StediClearinghouse / API-first healthcare EDI	Developer-first, API-native healthcare clearinghouse offering modern REST APIs for eligibility, claims, and remittance in place of legacy EDI tooling.	Stedi and shteg.ai share an API-first, developer-experience sensibility for clearinghouse functions. The structural difference is scope: Stedi provides the EDI/clearinghouse APIs as a clean building block, while shteg.ai extends the same identity through settlement and a hash-chained money ledger under one gate.

API-first / headless RCM

Company	Their public positioning	How shteg.ai differs (by design)
Candid HealthAPI-first / headless RCM	API-first, headless revenue-cycle automation with automated claim scrubbing, submission, and a configurable rules engine, marketed to engineering-led healthcare teams.	Candid’s public position is developer-friendly RCM automation that maximizes clean-claim throughput. shteg.ai’s propose-never-dispose and fail-closed doctrine deliberately constrains automation from disposing on its own, and puts compliance conditions inside the money authorization rather than in the claim rules layer.
AdonisAPI-first / RCM automation + intelligence	Revenue-cycle automation and intelligence platform using AI to automate eligibility, claims, and denials, with analytics positioned as an intelligence layer over billing.	Adonis foregrounds AI-driven autonomous resolution across the revenue cycle. shteg.ai treats agentic components as proposers behind a deterministic gate, so the differentiator is the reviewable boundary and the WORM audit trail rather than the degree of autonomous action.

The one thing to take away

shteg.ai is pre-production. This compares design, not market results.

No real dollar has ever moved through shteg.ai and no real PHI has ever flowed through it. This page compares design and approach — architecture plus a registered HIPAA clearinghouse identity (a real Type-2 organizational NPI) — not market results, traction, transaction volume, uptime, or customers, none of which shteg.ai claims.

No real dollar has moved. No real PHI has flowed.

What is real: the architecture — hash-chained ledger, settlement gate, and reconciliation waterfall, tested in the current build — the Type-2 organizational NPI and registered HIPAA clearinghouse identity, and the doctrine. We register capability as capability, never as traction.

Verified-greentested in the current build

Gatedawaiting a named human/legal gate

Every statement about another company reflects only that company’s own public positioning, described factually and without disparagement; there are no invented benchmarks, no head-to-head performance numbers, and no “we win” scorecards here. The incumbents named are established, in-market products with real, proven scale; shteg.ai is a system whose settlement gate, hash-chained WORM ledger, and fail-closed integrations are tested in the current build, while its production apply, AML program, money-transmission legal opinion, and FedNow certification remain genuinely gated on named human and legal steps. Read this as a comparison of how the systems are built, not of how they perform.

Read the honest status register See the platform architecture

Everyone sells a segment. We operate the whole path.

An EMR captures the encounter, a clearinghouse translates the claim, an RCM tool chases the payer, a processor moves the money — each owns one hop. shteg.ai runs the whole track on one ledger.

This page compares how the systems are built, not how they perform — shteg.ai is not yet in production, and the incumbents named here have real, proven scale.

Every statement about another company reflects only its own public positioning, stated factually and without disparagement.

How the field describes itself — and where shteg.ai differs.

Company

Their public positioning

How shteg.ai differs (by design)

NextechOphthalmology / specialty EMR + PM

Specialty-specific EHR and practice management for ophthalmology, dermatology, plastic surgery and med spa, positioned as an all-in-one platform with patient engagement and revenue-cycle services.

Nextech centers the specialty clinical and practice-management workflow. shteg.ai is not a competing specialty EMR; it treats the encounter as the start of a single loop that continues through claim routing and settled money on one hash-chained ledger, and it is itself a registered clearinghouse rather than connecting out to one.

ModMed (Modernizing Medicine)Ophthalmology / specialty EMR + PM

Physician-built, specialty-specific EHR (EMA) with adaptive learning, practice management, analytics, and ModMed-branded RCM services across specialties including ophthalmology.

ModMed’s public strength is the specialty clinical experience plus optional RCM services layered on top. shteg.ai’s differentiator is not the clinical UI but the deterministic settlement gate and covered-entity clearinghouse identity that make compliance a precondition of money movement rather than a service alongside it.

CompulinkOphthalmology / specialty EMR + PM

All-in-one specialty EHR and practice management (Advantage) for ophthalmology, optometry, and other specialties, with integrated billing and RCM offerings.

Compulink bundles clinical, PM, and billing within one specialty suite. shteg.ai’s design point is what happens at the money boundary — a fail-closed, six-condition gate on a WORM ledger — and an audit trail assembled as events happen rather than reconstructed from separate modules.

Company

Their public positioning

How shteg.ai differs (by design)

AvailityClearinghouse / health information network

One of the largest real-time health information networks, connecting providers and payers for eligibility, claims, remittance, and prior authorization, with a widely used provider portal.

Availity operates as a connectivity and routing network between providers and payers. shteg.ai holds the clearinghouse role too, but folds it into a single system that also owns settlement and audit, rather than sitting as a routing layer that hands off to separate RCM and payments systems.

Optum / Change HealthcareClearinghouse / connectivity + RCM network

A very large clearinghouse, connectivity, and revenue-cycle network (part of Optum/UnitedHealth Group) spanning claims, eligibility, payments, and analytics across the industry.

Change/Optum offers enormous, proven scale across many separately consumable services. shteg.ai makes the opposite bet at pre-production scale: consolidate the loop onto one ledger with one non-swappable settlement gate, and be explicit that it is architecture and clearinghouse identity, not traction.

WaystarClearinghouse / cloud RCM platform

Cloud-based revenue-cycle and clearinghouse platform covering claims management, denials, payer connectivity, payments, and the patient financial experience.

Waystar’s public emphasis is end-to-end RCM performance and automation across the revenue cycle. shteg.ai frames the same territory around a deterministic gate that fails closed and a propose-never-dispose boundary, prioritizing auditability and stop-on-doubt over straight-through throughput.

StediClearinghouse / API-first healthcare EDI

Developer-first, API-native healthcare clearinghouse offering modern REST APIs for eligibility, claims, and remittance in place of legacy EDI tooling.

Stedi and shteg.ai share an API-first, developer-experience sensibility for clearinghouse functions. The structural difference is scope: Stedi provides the EDI/clearinghouse APIs as a clean building block, while shteg.ai extends the same identity through settlement and a hash-chained money ledger under one gate.

Company

Their public positioning

How shteg.ai differs (by design)

Candid HealthAPI-first / headless RCM

API-first, headless revenue-cycle automation with automated claim scrubbing, submission, and a configurable rules engine, marketed to engineering-led healthcare teams.

Candid’s public position is developer-friendly RCM automation that maximizes clean-claim throughput. shteg.ai’s propose-never-dispose and fail-closed doctrine deliberately constrains automation from disposing on its own, and puts compliance conditions inside the money authorization rather than in the claim rules layer.

AdonisAPI-first / RCM automation + intelligence

Revenue-cycle automation and intelligence platform using AI to automate eligibility, claims, and denials, with analytics positioned as an intelligence layer over billing.

Adonis foregrounds AI-driven autonomous resolution across the revenue cycle. shteg.ai treats agentic components as proposers behind a deterministic gate, so the differentiator is the reviewable boundary and the WORM audit trail rather than the degree of autonomous action.

shteg.ai is pre-production. This compares design, not market results.