Zero external model exposure by default
Model execution is packaged for your infrastructure. PHI and sensitive claims fields do not need to cross your firewall.
Insurance claims AI strategy
Local AI controls for insurance claims workflows.
Pipeline Claims is designed to process raw claim PDFs and images inside the application while keeping consequential claim decisions under human control.
When an approved external model is used, locally deidentified text—not raw source documents or rendered images—may cross that provider boundary. Deployment, contracts, retention, and customer authorization still require diligence.
Where cloud-only assumptions need diligence
Provider boundaries must be evaluated explicitly.
A BAA or deidentification step is not the whole control environment. Claims teams still need to evaluate what data crosses each boundary, which services receive it, how it is retained, and what happens when confidence is low.
- Data ends up touching other people’s servers and tooling.
- Misconfigurations, credential leaks, or software mistakes can expose material in one weak link.
- And cleanup is expensive and slow when a breach happens.
Why redaction tools still fail
Deidentification quality is a control, not a guarantee.
Claims teams are not dealing with clean text. They are dealing with handwritten notes, scans, scans from mobile photos, and messy forms. That is where automated redaction can miss identifiers.
If sensitive content crosses an external-provider boundary, its handling depends on the approved service configuration and contract. Low-confidence material should remain review-required rather than being treated as safely transformed.
What local AI changes
You get speed and protection from one deployment model.
Human review still stays in control
AI supports structured extraction and decision support, but people keep final authority on claim actions, response conditions, and settlement posture.
Governed evaluation data
Authorized teams can evaluate and calibrate approved workflows against controlled datasets without treating automated deidentification as infallible.
In plain terms: claims teams can evaluate AI assistance with explicit data boundaries, documented controls, and human responsibility for consequential decisions.
For carriers and TPAs
Built for insurers with strict obligations.
- Works with internal security teams’ architecture standards.
- Can reduce exposure from raw-document upload pipelines and unnecessary transfer chains.
- Supports claims operations teams that need predictable governance and traceability.