Less than one FTE to operate a complete AI-native care stack — from patient intake through RTM billing, with a physician reviewing and signing every output before it touches a patient or a claim. The harness enforces that review at the schema level, writes every attestation to a 7-year WORM-locked audit chain, and produces FHIR R4 output automatically. You don't build physician governance; you inherit it.
Each brand solves a distinct problem. All three run on the same AI harness with the same physician governance model.
Worker-owned home care for aging families. AI generates care plans, schedules caregivers, and drafts letters of medical necessity for HSA/FSA reimbursement. A physician reviews and signs every LMN.
co-op.care →Nine AI agents for orthopedic practice management: missed billing detection, remote therapeutic monitoring, prior authorization, patient outcomes tracking, and referral capture. Connects directly to Epic, Cerner, and athena.
surgeonvalue.com →A physician review marketplace. AI companies submit clinical outputs. Physicians review and attest via a structured swipe interface. Every accept, modify, or reject generates FHIR-structured data and a signed audit record.
clinicalswipe.com →These are the unit economics SolvingHealth runs on — the same numbers a health system adopting the harness inherits.
AI generates the draft. A physician reviews, edits, and signs. The signature is the product — not the generation.
The SolvingHealth harness is an AI orchestration layer that wraps any clinical workflow. A single JavaScript embed routes requests to the appropriate AI model, enforces physician review requirements, and writes every attestation to a WORM-anchored audit chain. You don't need to build physician governance — you inherit it.
The shift is structural, not aspirational. Healthcare AI companies that generate outputs without a documented physician review trail face a simple problem: when a claim is challenged, a compliance officer asks for evidence, or a patient outcome is questioned, a policy document that says "physicians review AI outputs" is not a defense. A cryptographically verifiable ledger entry — physician NPI, timestamp, review duration, scroll depth, output hash — is. The harness generates that record automatically on every transaction.
We are an operator, not a vendor. SolvingHealth built this infrastructure to run its own care company, not to sell software to health systems. The proof of value is in our own P&L — the same P&L we open-book to any partner. Build trust through operations, then license the stack.
Physician sign-off is enforced by the database schema, not by policy. Review time (minimum 30 seconds wall clock), viewport activity (minimum 20 seconds foreground), and scroll depth (minimum 80% of the output) are all validated by CHECK constraints before a signature record is written. The AI output cannot reach a patient or a billing claim without a schema-enforced review event. Policy documents are not an OIG defense; database constraints are.
Every attestation produces structured FHIR R4 output — not a PDF, not a free-text summary. Home care Omaha System nursing assessment data maps to hospital-grade clinical records automatically, generating the kind of longitudinal data corpus that health systems and payers license. The data corpus is the long-term moat; it grows with every review and becomes more valuable as the network scales.
Daily SHA-256 digests of all decision ledger entries are written to Cloudflare R2 object storage with a 7-year WORM compliance lock. The next day's cron job verifies by reading back the digest. Every attestation — accept, modify, or reject — is indexed in the ledger with physician NPI, timestamp, review metrics, and the signed output hash. The ledger is OIG audit-ready from transaction one, not retrofit-ready at audit notice.
Compliance scoring is baked into the decision ledger — not a post-hoc legal check. Flat per-encounter fees (not revenue-share percentages), not referral-volume-tied. The billing architecture follows OIG Advisory Opinion 25-03 as a structural template for MSO-physician practice arrangements. Every transaction is structurally defensible before a compliance officer looks at it.
The thesis is simple: AI generates the clinical draft; a licensed physician reviews, edits, and signs before it touches a patient or a claim. Every step from generation to signature to audit record happens inside the harness — no stitching required. Here is what one letter of medical necessity looks like in practice.
Tap any box to isolate its connections. The harness in the center touches all of them.
The SolvingHealth harness is the professional-grade stack for clinicians building with AI. Physician governance baked in. FHIR-native output. No compliance consulting required.
You are an MD who has realized that the fastest way to change clinical practice is to ship software, not papers. You can write a system prompt. You can call an API. You need the infrastructure that makes what you build defensible.
JetBridge Harness is the production layer: physician attestation schema, OIG audit chain, FHIR R4 output, and AKS-clean billing hooks — pre-built so you can focus on the clinical problem you actually want to solve.
"We built this to run our own care company. The same rails that generate $520K/year in LMN revenue are the same rails you license. Operational proof, not a sales deck."
Organizations that want to plug in — whether you're a health system, a payer, or a developer — have a named lane with named economics.
We work with health systems, payers, device companies, and AI developers who want physician-governed AI infrastructure they don't have to build from scratch.