OmniAI reviews the longitudinal patient record before the visit and surfaces the conditions, evidence, and quality gaps most likely to be missed. Clinicians confirm what is clinically true, documentation is completed in workflow, and risk capture becomes defensible by design.
See the right diagnoses. Capture them with proof. All in your workflow.
Best fit for risk-bearing groups, MA plans, and ACOs with 5,000+ lives at risk.
Results observed in a 90-day pilot across 14 PCPs and 2,847 visits. Financial impact is projected annualized HCC value based on the observed pilot population and should be validated against each customer's payer mix, contract terms, coding rules, and audit policies.
One platform, four jobs to be done. Pick the view that matches how you'll be measured this year.
Clinician-in-control evidence at the point of care. No new alerts. No black-box decisions.
For physicians → Finance & VBCPer-member economics, payback, and audit defensibility your finance team can model.
For health systems → CMIO & InformaticsEmbedded inside Epic and Oracle Health. No new tab, no separate login, no install.
See the product → Practicing PCPsReviewing a flag takes ~15 seconds. Templates save typing per condition. You stay in control.
FAQ for physicians →A full schedule. Incomplete charts. Open quality gaps. Chronic conditions that should be reassessed but are buried across notes, labs, medications, prior encounters, and claims history.
In value-based care, patient acuity and quality performance depend on what is clinically assessed and documented during the visit. But clinicians do not have the time to manually rebuild every chart, chase every historical diagnosis, and close every care gap while still caring for the patient in front of them.
This is not a clinician problem. It is a workflow problem.
Bottom line: clinicians do not need another task. They need an intelligent workflow that prepares the chart, surfaces what matters, and closes the loop before anything gets missed.
Most "risk adjustment" tools start from the code. We start from the patient record and the encounter where the clinician can actually act.
Coders look for what was already documented. OmniAI surfaces what should have been documented, while the patient is still in the room.
Net difference: evidence is created at the point of care, not chased weeks later.
NLP tools and scribes capture what the clinician says. OmniAI brings forward what the longitudinal record shows the clinician should consider.
Net difference: changes the visit, not just the note.
FHIR plumbing, longitudinal feature engineering, evidence-chain UX, and audit-ready output are many quarters of engineering before the first useful flag reaches a clinician.
Net difference: pilot in days, not quarters.
OmniAI prepares the chart before the visit, guides the clinician during the encounter, and closes the loop before the day ends.
OmniAI reviews the next day's schedule and organizes the longitudinal record, including notes, labs, medications, prior visits, problem lists, and claims where available. It identifies the high-impact conditions and quality gaps most likely to be missed, then links each flag to supporting evidence.
Clinician outcome: the day starts with the chart already organized.
Evidence-backed flags appear inside the EHR workflow through SMART on FHIR where available. Each flag shows why it matters, what evidence supports it, what documentation is missing, and what action the clinician can take. Quality gaps appear in the same view, with the patient's current value, target, and suggested next step where applicable.
The clinician accepts, edits, or dismisses. OmniAI never replaces clinical judgment.
Clinician-confirmed items flow into documentation with the evidence chain attached: diagnosis, assessment, supporting data, and clinical reasoning. Coders receive a cleaner encounter, and submitted diagnoses carry the support needed for review.
Organization outcome: fewer retrospective queries, cleaner charts, and a more defensible revenue cycle.
It feels like a resident pre-charted the patient and brought me the exact evidence I needed. - Pilot physician
OmniAI is designed for organizations that need to improve value-based performance without creating clinician burden, audit exposure, or black-box decision making.
Every recommendation is accepted, edited, or dismissed by the clinician.
OmniAI shows the supporting data behind the suggestion, not just a diagnosis label.
The product starts with clinical evidence and patient context, not a code-first workflow.
Documentation is tied to clinician-confirmed assessment and evidence.
Outputs can be reviewed for acceptance rate, dismissal patterns, evidence quality, and downstream audit support.
Risk capture, quality gaps, and clinical context appear in the same workflow.
Centers in Houston, New England, and Chicago.
*Important qualifier: these pilot results are early signals, not guaranteed outcomes. Each customer should validate impact against its own patient population, payer contracts, risk model, coding policies, and compliance standards.
I caught a CKD Stage 3a I would have completely missed. The patient is now on appropriate therapy and her eGFR stabilized. - Pilot physician
OmniAI helps risk-bearing organizations improve documented acuity, reduce retrospective chart chasing, and create cleaner, more defensible submissions. The financial case is built on three levers:
For clinical leaders, OmniAI is designed to reduce cognitive load and improve encounter readiness. It does not ask the physician to become a coder. It brings forward the evidence already present in the record and lets the clinician decide what is clinically true today.
Built for the controls your security, privacy, and compliance teams already require.
Patient data stays inside your environment. No PHI is used for model training without an executed BAA and your explicit governance approval. OmniAI outputs can be reviewed for acceptance rate, dismissal patterns, and downstream audit support.
In 30 minutes, we'll show OmniAI inside an EHR-style workflow with real clinical scenarios. No long deck. No abstract AI talk. Just the product, the visit, and the evidence chain.
Best fit for risk-bearing groups, MA plans, and ACOs with 5,000+ lives at risk.
