SciAI is designed for research integrity. From content firewalls to artifact provenance, every layer is built for auditability and trust.
Multiple security layers protect your research data and ensure process integrity.
All external content (PDFs, web pages) is sanitized before LLM processing. Known prompt injection patterns are detected and redacted.
Data is tagged with sensitivity levels that determine where it can be processed. Sensitive data routes to appropriate models.
Every artifact is SHA-256 hashed at creation. Hashes are verified on access. Tampering is detectable.
Artifacts can be locked to prevent modification. Locked changes require formal deviation workflows.
Sensitive operations require explicit human approval. No silent execution of high-impact actions.
Complete history of all runs, approvals, checkpoints, and changes. Full transparency for review.
AI agents can make mistakes. Language models hallucinate. Statistical methods require human judgment to apply correctly.
What we do guarantee: SciAI captures the process with integrity. You can see what was done, when, by which agent, and whether it was reviewed.
Scientific correctness remains your responsibility. We make it possible to prove your process was rigorous—not that your conclusions are right.
We're transparent about what's implemented now and what's on the roadmap.
For institutions that require on-premises deployment, SciAI can be self-hosted in your infrastructure with full data sovereignty.
Contact Enterprise SalesBook a demo and we'll walk through our security model in detail.
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