Platform
One intelligence layer for the care plan and the patient.
reCare.ai shows whether expected care is on track while also recognizing meaningful patient-level change. The result is one evolving context for care gaps, rising risk, and the follow-up needed to act before either becomes an avoidable outcome.
Reconcile expected care, completed events, future plans, and patient-specific change.
The operating model
Understand both what should happen and what is changing.
One side of the platform reconciles the intended care path: what should happen next, what already happened, and what is scheduled or otherwise planned.
The other side interprets new longitudinal signals against the patient’s own recent history and current plan. That makes it possible to distinguish a care-plan exception from a patient who is meaningfully changing—and to support the appropriate workflow for either.
What reCare.ai can do today
Concrete capabilities for real healthcare workflows.
Ingest clinical and operational events from existing systems
Normalize events into longitudinal patient context
Compare expected care against completed and planned care
Detect missing steps and meaningful patient-level changes
Trigger approved outreach and coordination workflows
Track whether the expected next step occurred
Preserve the evidence behind each surfaced exception
Integration patterns
The integration footprint is scoped to the workflow. A referral-closure deployment does not need the same data as a post-discharge transition workflow.
Platform capabilities
Each capability answers a different part of the same operating question.
Patient Intelligence
Build an evolving patient-level view that includes what happened, what is planned, and what has changed.
Explore →Care Leakage Detection
Find expected care that has no completed or planned event, or a care plan that is incomplete before the gap becomes a failure.
Explore →Risk & Longitudinal Intelligence
Recognize meaningful change using the patient’s own longitudinal context, not only a static population score.
Explore →Engagement & Automation
Use patient context to support outreach, coordination, scheduling, navigation, escalation, and human review.
Explore →Integrations
Connect the clinical, operational, communication, device, and event data needed to understand the care journey.
Explore →Deployment principle
Start with one measurable problem, not a giant data project.
A deployment can begin with one defined problem and the evidence needed to understand it—for example referral closure, post-discharge follow-up, chronic-care follow-through, or identifying patient-level changes associated with rising readmission or acute-care risk. The data footprint can expand as the workflow proves value.
Platform FAQ
Common questions from healthcare teams.
What does reCare.ai actually do?
reCare.ai is a patient-intelligence platform that connects longitudinal clinical and operational signals, shows whether expected care is on track, recognizes meaningful patient-level change that may indicate rising risk, and supports approved follow-up workflows.
Does reCare.ai replace an EHR or care-management platform?
No. reCare.ai is designed to sit across existing systems and use their events as evidence about the patient journey rather than replace the systems of record.
How does reCare.ai integrate with healthcare systems?
Integration patterns can include HL7 FHIR, APIs, webhooks, event feeds, scheduling and referral data, claims, and structured data files, depending on the workflow.
Does reCare.ai make clinical decisions autonomously?
reCare.ai is designed to support operational workflows and patient intelligence while preserving human review where clinical judgment, policy, or uncertainty requires it.
Move from signals to action
See whether care is on track, and when the patient is changing.
Bring us a high-value workflow, a care-plan problem, or a population where earlier visibility into patient change could prevent an avoidable outcome. We’ll show you how the intelligence layer fits.