Compliance Certain. Context Preserved.™
HIPAA-Compliant Intelligence Platform for Unstructured Medical Records
Zero-config local redaction that transforms any patient record into LLM-ready context — unlocking frontier AI reasoning while maintaining complete PHI/PII isolation and audit transparency.
Healthcare organizations need advanced AI reasoning to synthesize patient histories, streamline intake, and support clinical decision-making — but frontier LLMs pose unacceptable PHI exposure risks.
Aegis Abstract eliminates this trade-off. Use the most powerful reasoning models available—safely—while maintaining complete HIPAA compliance and audit transparency.
Existing solutions force an impossible choice: use weak, narrow-domain models that are HIPAA-safe but lack reasoning depth, or risk compliance with powerful external models.
Aegis Abstract accepts any patient record—lab reports, clinician notes, treatment histories, mixed-format PDFs—and with zero human preprocessing, locally extracts and redacts all PHI/PII using onboard NLP.
The redacted data is converted to LLM-friendly Markdown with semantic label tokens (preserving clinical context while removing identifiers), then safely passed to frontier models for advanced summarization, reasoning, and insights abstraction.



Consolidate dozens of records into organized summaries. Dramatically reduce practitioner time on chart review.
Synthesize multi-visit histories for specialists. Provide HIPAA-compliant summaries for consultations.
Use frontier LLMs to surface patterns, flag gaps in care, suggest diagnostic paths—safely.
Generate clean, de-identified clinical narratives for payer submissions while maintaining compliance.
Normalize heterogeneous sources for BI and cohort analysis with privacy guarantees.
Prepare de-identified datasets for trials and registries with longitudinal consistency.
The output isn't a redacted PDF—it's clinical intelligence. Generates consolidated summary reports from dozens of documents.
No masking, no templates, no training. Works on any format: scanned images, digital PDFs, tables, handwritten notes.
100% local processing—no sensitive data leaves your environment. Detects all 18 HIPAA PHI identifiers plus contextual PII.
Semantic label tokens ({{PATIENT_NAME}}, {{DOB}}) preserve clinical context so LLMs can reason effectively.
Unlock SOTA reasoning models (GPT-4, Claude) on fully anonymized, LLM-ready Markdown—safely and compliantly.
Audit Viewer lets users trace any report phrase back to the original source PDF for verification and compliance.
Transform hundreds of pages into timely summaries clinicians actually use. Enable comprehensive patient history consideration without the time burden—improving care decisions and outcomes.
Use the most advanced reasoning models—safely. Move beyond narrow medical models with limited capability.
Reduce intake processing costs by 75%+ and save hours per patient. Automate consolidation that would otherwise require manual chart review and documentation prep.
No templates, no training, no labeling. Deploy in days, not quarters.
Seamlessly integrates with existing EHRs via FHIR R4. Broker specialized tools via SOTA orchestrator while maintaining HIPAA firewall across all transactions.
Strictest data locality for maximum control and complete data sovereignty
Customer-managed keys with cloud LLM access and scalability
Local redaction + cloud SOTA models on anonymized text only
Aegis Abstract eliminates the trade-off between compliance and intelligence. Transform any patient record into HIPAA-compliant, LLM-ready data—unlocking SOTA summarization that saves practitioners hours per patient.
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