Zero Data Retention Security Architecture

Client-Side Volatile Memory Execution

Manuscript source text, equations, and experimental findings are parsed locally inside the browser using Web Workers and WebAssembly. No draft files or author prose are ever saved to backend database storage.

Zero Model Training & Ingestion

Unpublished manuscripts and research findings are never utilized to train, fine-tune, or evaluate foundation AI models. API terms with upstream inference partners strictly prohibit customer data retention for model development.

Targeted Bibliographic Lookups

Registry cross-references against Crossref, OpenAlex, Semantic Scholar, and PubMed transmit only isolated citation identifiers (DOIs) and claim sentence pairs over encrypted TLS 1.3 channels.

The manuscript is loaded into volatile browser memory via local file handle or direct editor input. Non-compiled comments are handled safely, and mathematical environments are quarantined into read-only token blocks to prevent syntax corruption.

Sentence boundary detection identifies claim candidates directly on your local machine. Citations are mapped against the local bibliography without sending manuscript content to third-party endpoints.

When an author triggers verification, query parameters are cross-referenced with public academic registries over encrypted channels. Query responses exist ephemerally during the active session.

Closing the browser tab releases in-memory data structures. Author prose is never written to disk or preserved in server logs.

Grant Software Expense Eligibility

Researcher Pro and Lab Multi-Seat licenses qualify under standard scientific computing and research software expense categories for NSF, NIH, Horizon Europe, and university discretionary grant budgets.

Pre-Publication Confidentiality

Client-side execution guarantees that embargoed findings, patent disclosures, and proprietary manuscripts remain under the continuous custody of the researcher.