Relationships
Meaning emerges from relationships. Patients are not isolated data points. Care unfolds across time, people, and providers—with the patient at the center.
What relationships means to us
Healthcare data is relational by nature. A diagnosis is connected to symptoms, tests, and treatments. A medication is connected to a prescriber, a condition, and potential interactions. An insurance claim is connected to a procedure, a policy, and an outcome.
When you flatten these relationships into documents or lose them in silos, you lose the meaning. The fact exists, but the context that makes it actionable disappears.
Our clinical knowledge graph encodes health as a network of explicit, queryable relationships so nothing meaningful is lost. We preserve the connections that matter because understanding requires structure, not just data.
Why relationships matters
Data without context is noise. The same lab value means something entirely different depending on what medications the patient is taking, what conditions they have, what happened last week.
Context
Isolated facts are ambiguous. Relationships provide the context that transforms data into understanding—the "why" behind the "what."
Causality
Understanding cause and effect requires tracking how events connect over time. Relationships encode the causal chains that explain why things happen.
Completeness
Fragmented views lead to fragmented care. Anchoring every relationship to the patient means a complete history follows them across providers, so nothing falls through the cracks.
Care is inherently relational
A patient's health is not a collection of independent facts. It is a story unfolding over time, connecting symptoms to diagnoses, treatments to outcomes, specialists to primary care, clinical reality to financial access.
Current EHR systems treat data as rows in tables. They store facts but lose relationships. When a clinician opens a chart, they must mentally reconstruct the connections that the system failed to preserve.
Silos destroy relationships
Healthcare is fragmented by design—different EHRs, different institutions, different systems that never reconcile. Each silo holds a partial view. The relationships that connect them are lost in translation.
This fragmentation is not just inefficient; it is dangerous. Critical connections are missed because no single system holds the complete picture. Serelora reconnects what fragmentation has torn apart by placing the patient at the center, so their complete history follows them across every provider and care team.
How we build relationships into the product
Clinical knowledge graph
Every record becomes part of a clinical knowledge graph where clinical, administrative, and financial data are connected entities. Diagnoses, medications, labs, encounters, claims, and SDOH are linked through explicit, queryable relationships that preserve temporal order, causality, and dependency.
- Relationships between entities made explicit and queryable
- Temporal ordering preserved across all data
- Causal chains explicitly encoded as edges
Claims Graph demo
EHR-agnostic architecture
We ingest any format from any source—patient uploads, clinical notes, claims, intake forms, labs, and SDOH—with no interoperability requirements. The source does not matter; what matters is that relationships are preserved and anchored to the patient across systems.
- Any format, any source, no interoperability requirements
- A complete history that follows the patient across providers
- Provenance tracking for every data point
Data integration demo
Agents that traverse the graph
Specialized agents query the connected graph to draft notes, billing codes, and prior authorizations. Every output links back to the exact graph node and supporting literature that generated it, and nothing executes without clinician approval.
- Specialized agents query the connected graph
- Every output links to the graph node behind it
- Clinician approval required before execution
Action Graph demo
We do not just store data. We preserve the connections that give it meaning.