Real-time visibility across the care ecosystem. Early detection of anomalies and systemic risk. Designed for government-scale welfare systems.
Multiple providers, service types, and funding categories per participant.
270,000 providers with inconsistent billing behaviours impossible to monitor manually.
Anomalies go undetected until significant financial leakage has occurred.
Current tools identify problems months after claims are processed and paid.
The critical gap: No real-time understanding of system-wide behaviour. The NDIS operates without continuous visibility into provider networks, billing trends, or emerging systemic risk.
CareIntegrity.ai is not another compliance tool. It is a foundational intelligence layer — purpose-built to provide continuous, system-wide visibility across the entire care ecosystem.
See providers, participants, workers, and services as one connected system.
Identify risk signals before they become financial losses.
Always-on oversight, not periodic audits.
Each layer builds on the one before it — transforming raw claims data into actionable system-level risk intelligence.
Maps providers, participants, workers as a connected network. Detects closed-loop money flows, shared staff, and controlled clusters.
Tracks provider behaviour changes over time. Catches impossible acceleration, billing spikes, and service mix shifts.
Validates claimed care against time, staffing, and geography. Asks: "Is this care delivery physically possible?"
Graph Neural Networks, node embeddings, unsupervised anomaly detection, and community detection produce a composite risk score.
Unlike single-dimension fraud checks, CareIntegrity.AI analyses the entire ecosystem simultaneously.
Maps every relationship. Detects closed-loop money flows, invoice cycling, and provider clusters.
Tracks provider fingerprints over time. Catches impossible acceleration -- 5 to 80 participants with no new staff.
Models human physical limits. Workers at two locations simultaneously. 24-hour billing days. Impossible travel.
AI converts providers into behaviour vectors. Detects when a therapy provider suddenly becomes SIL-heavy.
Generates "normal care" baselines per participant. Compares real billing to detect over-servicing.
Graph community detection finds provider cartels -- shared staff, common addresses, referral loops.
Every invoice scored against baselines, peer averages, workforce constraints, and geographic feasibility.
Officers define custom detection rules with conditions, operators, and AND/OR logic.
Review evidence, approve penalties, full forensic drill-down to individual claims.
Printable compliance reports with recommendations and financial summaries.
Geographic fraud hotspot visualisation with click-to-inspect.
Track fraud detected, penalties issued, collection rates, and recovery.
10 fine codes with severity multipliers. Auto-issue with email notifications.
6 roles with 35+ permissions, full audit trail, and user management.
12 compliance standards with automated and manual checks.
Anonymous tip-off submission with investigation workflow.
Active surveillance with notes, priority levels, and review dates.
Real-time awareness across the entire scheme. See what's happening now, not six months ago.
Prioritised alerts replace random audits. Teams focus on highest-risk entities first.
Systemic issues caught early. From months to minutes.
Reduction in scheme leakage, directly improving sustainability and protecting taxpayer investment.
CareIntegrity.ai is not a point solution — it is the beginning of unified integrity infrastructure across all government-funded care.
Disability care ecosystem
Senior support systems
Medical & clinical services
Unified integrity layer
Live demo with real detection results, 8 AI engines, and full enforcement workflows.