Move from reacting to health data to anticipating clinical events before they happen.
Interoperly delivers real-time infrastructure powered by Causal AI and a living Digital Twin, transforming fragmented, multimodal data into clear, actionable foresight that scales across care teams and organizations.
Every decision is transparent, auditable, and built to respect patient data sovereignty, by design, not by policy.
We are the real-time intelligence layer between your data and your decisions. Interoperly transforms fragmented clinical signals into causal, decision-grade insight, so teams can act earlier, with confidence.
Interoperly is not an EHR replacement and not a black-box AI system. We integrate with your workflows and deliver explainable, auditable intelligence, keeping clinicians firmly in control.
We handle the complexity of connection. Our three-layer engine transforms fragmented health data into decision-grade intelligence you can trust.
It's not enough to predict outcomes. We use Causal AI and physiological simulation to explain why events happen and model what-if scenarios, moving clinical decisions from correlation to causation.
We normalize high-velocity clinical streams into clean, FHIR R4–native resources in milliseconds, creating a consistent, real-time source of truth across systems.
We unify clinical records with real-world health signals: from EHRs and medical devices to consumer platforms like Apple Health, Google Fit, and Oura, so no critical context is lost and no patient is reduced to partial data.
This is the engine behind every prediction, intervention, and decision at clinical scale.
Predictions without explanation don't belong in clinical care. Interoperly identifies the root cause behind every signal, showing clinicians why a risk is emerging, not just that it exists, so decisions are grounded in evidence, not intuition.
Care shouldn't rely on trial and error. Interoperly continuously simulates a patient's physiological state, projecting outcomes up to 90 minutes ahead, so teams can evaluate interventions virtually and act before harm occurs.
Purpose-built capabilities that apply real-time clinical intelligence to healthcare's most complex operational challenges.
Modernize pre-authorization workflows. Our Multimodal AI instantly validates medical necessity against payer rules, reducing administrative friction while preserving clinical oversight.
Use high-fidelity Digital Twins to simulate patient outcomes and generate Synthetic Control Arms, accelerating clinical insight across diverse populations without waiting years for trial data.
Detect physiological anomalies in real time and trigger interventions 30–90 minutes before an acute event, powered by causal inference, not correlation.
Enterprise-grade infrastructure designed for reliability, interoperability, and clinical trust.
Our distributed microservices architecture processes clinical events in real time, ensuring signals flow reliably from ingestion to decision without bottlenecks or delays.
We ingest and normalize structured and unstructured data: FHIR R4, HL7 v2, voice, documents, and images, into a unified clinical context without manual intervention.
End-to-end encryption, immutable audit logs, and standards-based authentication are built into the platform, supporting compliance from day one, not as an afterthought.
Our cloud-native orchestration supports elastic growth and resilient deployments, allowing the platform to scale with patient volume and operational demand.
async def process_stream(event: HealthEvent): # 1. Normalize to FHIR R4 fhir_resource = await fhir_converter.transform( event.payload, standard="R4" ) # 2. Run Causal Inference causal_graph = await dowhy_engine.infer( treatment='medication_x', outcome='glucose_variability', confounders=['sleep', 'stress'] ) # 3. Trigger Payer Workflow if causal_graph.effect > THRESHOLD: await payer_gateway.submit_auth( fhir_resource, evidence=causal_graph )
Enterprise-grade governance designed to protect patient rights, satisfy regulators, and earn long-term trust.
Patients retain control over their health data through configurable access, retention, and sharing policies, aligned with clinical and regulatory requirements.
Consent is enforced at the data-field level, ensuring every use of patient data aligns precisely with what was authorized, automatically and continuously.
Every data point is fully traceable, from origin through transformation, creating a complete, immutable audit trail you can query at any time.
Patients can withdraw consent or request deletion with a single action, propagated consistently across the platform to prevent residual or orphaned data.
We built a fully operational diabetes care platform to demonstrate how Interoperly performs under real clinical conditions.
This production system handles continuous CGM streaming, sub-minute inference, and real-time interventions, achieving 96.93% Clarke Zone A accuracy in live patient workflows.
Interoperly exists to amplify clinical intelligence with AI, not replace it.
"I approach healthcare as a development challenge, applying economic incentives and Causal AI to modernize the fragmented systems we all rely on."
Partner with us to bring real-time, decision-grade clinical intelligence to your patients, providers, and organization.