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Platform

Built from the ground up
for institutional intelligence.

Eight purpose-built components that work together to capture, aggregate, and compound intelligence, while keeping every byte of data within your walls.

On-premisePrivate cloudAir-gappedFHIR nativeAudit-first

Integrates with

EpicCernerMeditechOracle HealthHL7 FHIR R4DICOMHL7 v2

and more

Components

Eight components. One coherent system.

01

Learning Kernel

The core engine that continuously adapts the ILM to new interactions. Incremental fine-tuning without catastrophic forgetting. Every documented decision sharpens the model without erasing what it already knows.

Continual learning via gradient accumulation
Forgetting-resistant weight updates
Configurable learning rate per user tier
02

Real Time Data Fabric

A high-throughput event stream that captures every clinical or workflow event in real time. The connective tissue between your existing EMR and the AIIM intelligence layer, no batch jobs, no lag.

HL7 FHIR R4 native
Proprietary EMR adapters available
Sub-50ms event propagation
03

Digital Twins

A dynamic computational model of each patient, maintained in real time as new data arrives. Not a static snapshot, a living representation that evolves with every interaction, test, and clinical decision.

Continuous longitudinal update
Multi-modal data integration
Clinician-interpretable state representation
04

Knowledge Graph

A structured representation of clinical relationships, institutional protocols, and population patterns. Contextualises ILM outputs by grounding them in verifiable institutional knowledge.

Institutional protocol encoding
Ontology-aligned (SNOMED, ICD-11, LOINC)
Dynamic edge updates from new evidence
05

AI Agents

Autonomous task agents that orchestrate complex clinical workflows, documentation, care pathway selection, alert triage, with full human oversight and one-click override at every decision point.

Human-in-the-loop mandatory
Multi-step workflow orchestration
Audit-logged action chains
06

Explainability

Every AIIM output ships with a complete reasoning trace. Not post-hoc rationalisation, step-by-step decision logic in plain language, reviewable by any clinician, auditor, or regulator.

Natural language reasoning chains
Evidence citation with source linking
Confidence intervals on every suggestion
07

Security

Zero-trust, zero-egress architecture. Data is encrypted at rest and in transit. All model weights remain within your network perimeter. No AIIM engineer can access your data or your models.

AES-256 at rest, TLS 1.3 in transit
Federated computation, raw data never aggregated
SOC 2 Type II ready deployment
08

Observability

Full-stack operational visibility into every AIIM component. Model performance, data quality, clinical adoption, workflow efficiency, all in a single pane, with configurable alerting.

Real-time performance dashboards
Data quality scoring per source
Clinical adoption and outcome tracking

The Guarantee

Your data never leaves.
Not once. Not ever.

AIIM is deployed entirely within your network perimeter. Your patient data, your clinical records, your model weights, all remain under your control, in your jurisdiction, forever.

The federated learning that builds INLMs and SLMs operates on gradient updates, mathematical signals, not data. No raw records are ever shared.

Zero egress

Raw data stays in your network. Always.

Jurisdiction-native

Deployed in your country, under your law.

Full audit trail

Every AI output logged, timestamped, reviewable.

Clinician override

Every suggestion is overridable. No black boxes.

Bring us your architecture questions.

Every deployment is designed to fit your infrastructure, not the other way around.

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