Prior authorization and referral workflows in healthcare are complex because they rely on data spread across multiple systems. Patient records live in EHRs, authorization details sit in revenue cycle platforms, payer rules are housed in external portals, and care coordination happens in separate tools.
Teams are responsible for reviewing documentation, interpreting payer requirements, and making decisions with incomplete context. This slows down approvals, increases the likelihood of denials, and adds administrative overhead across clinical and operational teams.
Delays in authorization directly impact treatment timelines. Incomplete submissions lead to rework. Manual routing of cases creates bottlenecks. Even when organizations have visibility into these issues, the process still depends on human coordination across systems.
Syntes AI provides a unified layer that connects clinical, administrative, and payer data into a single, continuously updated context.
At the core of the platform is a live knowledge graph that links patient records, authorization history, payer policies, and referral data. This creates a shared foundation where all relevant information is connected and accessible in real time.
On top of this foundation, AI agents operate across workflows. These agents analyze data in context, apply policy logic, and support decision-making throughout the authorization process.
The system continuously evaluates each case, surfaces gaps in documentation, and supports next steps based on historical patterns and payer-specific behavior.
Each step is supported by the full context of the case and aligned with defined policies.
Healthcare organizations gain a more coordinated and efficient authorization process.
The result is a process where decisions are informed by complete context and supported by systems that can coordinate actions across the workflow.
