If you're a health informaticist, data architect, or technical lead, you live in a world of dirty data. You've been promised interoperability for decades, but what you got was plumbing. And as you know better than anyone, plumbing that moves broken data just gives you... faster broken data.
The real crisis isn't connectivity. It's the L3 Semantic Gap: the chaos of unstructured notes, non-standard HL7v2 messages, and custom "Z-segments" that lock away 80% of essential clinical data.
At Kypspr, we don't move data. We refine it.
Our core IP is the L2 Semantic Data Refinery, an AI-powered engine obsessed with fidelity. Its singular purpose is to ingest this chaos and produce a perfectly structured, auditable "Golden Record view".
This is not a simple ETL job. It requires a non-negotiable, bifurcated "dual-vector" AI strategy. Here’s how it works.
Pipeline A: The "AI-Assisted, HITL" Mapping Engine (For Structured Chaos)
This pipeline is built to master the nuances of high-volume, structured-but-chaotic data, most notably HL7v2 messages. A generic mapper fails because it can't handle the decades of customization (like Z-segments) unique to every health system.
Our approach combines AI with your expertise:
- AI-Assisted Mapping: Our proprietary models—built on Google Cloud Dataflow for robust, stateful streaming—perform the initial, high-velocity translation.
- The HITL Validation Module: This is where you, the subject matter expert, come in. Our "AI-Assisted HITL Validation Module" is a customer-facing tool that flags low-confidence mappings or new Z-segments. It proposes a translation, and your team validates it.
Pipeline B: The "Narrative-to-Structure" Engine (For Unstructured Chaos)
This pipeline tackles the 80% of data locked in narrative text. Using a combination of Google Healthcare NLP API and custom Vertex AI models, this engine forensically analyzes unstructured clinical notes to find, extract, and structure the critical elements—diagnoses, labs, and medications.
The Guiding Principle: Uncompromising Fidelity
We never alter the original source of truth. Our mission is Translation, Fidelity, and Clarity. The L2 Refinery produces a "clean_fhir_stream" that is a provably accurate, auditable view of the source data. For compliance, our UI always shows the original source data alongside the proposed "Golden Record," ensuring a human (you) remains the final validator.
How We Get Smarter: The Compliant Feedback Loop
The HITL Validation Module does more than just ensure accuracy; it’s part of our compliant MLOps pipeline.
- HITL Validation: Your team validates a mapping for a localized "dirty data" segment.
- DLP Pipeline: This validated mapping data is processed by a Cloud DLP De-Identification Pipeline within the secure boundary.
- Federated Learning: The resulting de-identified, non-PHI data is used to retrain and improve the global AI model.
This Federated Learning (FL) framework is our definitive, high-trust solution. It allows our core IP to get smarter and more accurate without our team ever seeing your raw PHI.
The Result: A "Wedge" You Can Trust
The L2 Semantic Refinery is the engine inside our Kypspr API Sandbox. We invite your team to prove it. Our "Data Uploader" tool lets you input your dirtiest data and (under a mandatory BAA) get back a clean, validated FHIR output instantly.
Stop trying to plumb the chaos. It's time to refine it.