Platform
Ravisant converts interoperable clinical data into governed, explainable guidance for clinicians and measurable population intelligence for health-system leaders.
The clinical intelligence engine
Ravisant normalizes diagnoses, laboratory results, medications, observations and other patient facts into a consistent clinical model. Governed evidence-based rules evaluate those facts and identify care opportunities, exclusions, contraindications, monitoring needs and other actionable gaps in care.
Use data from existing health systems and standards-based interfaces.
Apply governed clinical and population-health logic.
Identify gaps in care, risk and the populations that matter most.
Route insight into action and roll outcomes back up.
Explainability
The patient facts, the rationale, the evidence and the rule version behind the recommendation — all of it in the context of the patient, and all of it traceable to the record. Nothing is hidden and nothing is automated away.
The clinician remains the ultimate decision-maker, and can override anything.
Governance
Every rule sits behind a certification gate. Until your named medical director signs it, it stays inactive — and invisible at the point of care.
Clinical logic is safety-critical. Ravisant treats it that way.
Evidence-based guideline definitions are configurable and version-controlled outside core code. Routine approved rule updates do not require a software release — but they still require clinical validation, regression testing, approval and controlled publication.
What the population-health team sees
A panel, a district, a region or a nation. Color-coded tiles reveal the distribution of gaps in care and make it easier to identify where interventions, outreach or policy attention are needed. Drill down from any number to the patients producing it.
Architecture
Ravisant is one platform, organized as three modules. The first, Clinical Intelligence & Governance, is the engine: it reads the clinical record and produces the explainable clinical logic. The other two — Care Coordination and Population Intelligence — run on that logic and put it to work, one patient by patient, the other across whole populations.
Module 1 · The engine
Normalizes clinical data, applies approved and version-controlled evidence-based rules, and surfaces explainable gaps in care while the patient is still in the room.
Certification, versioning and release of clinical rules stay under client control. Everything the other two modules show is produced here.
Roles: Clinician · Clinical Lead · Required
Module 2 · Powered by the engine
Turns identified gaps in care into a prioritized outreach worklist with named owners, assignment and closed-loop disposition.
Coverage continues when a coordinator is away. A supervisor view shows team workload, connect and closure rates, and the cases at risk of missing their follow-up window.
Role: Care Coordinator
Module 3 · Powered by the engine
Aggregates the same approved rules across populations, programs and facilities, so leaders see where care is on track and where it is not.
At national scope it adds the Ministry Administration tier.
Roles: Population Health Officer · Ministry Administration
Care Coordination and Population Intelligence are independent of each other. Take one, the other, or both — together or in phases, on your own timetable. Neither runs without the engine.
A ministry of health and a clinic or health network draw on the same three. Only the scope differs — national for a ministry, its own network for a clinic or health network. National command is not a separate product; it is Population Intelligence at national scope.
Care Coordination
Identified gaps in care become a prioritized outreach worklist with named owners, assignment, coverage when someone is away, and closed-loop disposition — so you can answer, for any patient, what was due, who took it and what happened.
Trust by design
Your named medical director certifies every rule and every threshold before it reaches a clinician. An unsigned change does not go live.
Clinical logic is safety-critical. Evidence-based guideline definitions are configurable and version-controlled outside core code. Routine approved rule updates do not require a Go engineer or a full software release, but still require clinical validation, regression testing, approval and controlled publication. Core-code changes follow the normal software release process.
Security and operational controls remain governed through encryption, least privilege, MFA/SSO, RBAC/ABAC, monitoring, recovery and observability.
Operational roles
Common questions
Every recommendation shows its reasoning: the rule that fired, the version of that rule, the guideline it came from, and the patient data that triggered it. A clinician can see why, and a reviewer can reconstruct it afterwards.
Your own clinical leadership does. Rules are drafted, certified, versioned and released under your control. Ravisant does not change clinical logic on your behalf.
There is no opaque model deciding care. The logic is written down, version-controlled and auditable, so every recommendation traces back to an approved rule rather than to a statistical output nobody can inspect.
No. It reads the clinical data you already hold through interoperability standards, applies your approved rules to it, and returns the result into the workflow your teams already use.
Deployable by ministries and clinics worldwide.
