Security and Privacy in AI: A Regulatory Imperative
Security is often discussed in AI conversations, but in regulated industries, it is non-negotiable.
Many generic AI integrations operate through system-level access. An LLM may interact with data using elevated permissions that do not reflect individual user rights. In some models, content is processed externally.
This creates significant exposure.
The Risk Landscape
In life sciences environments, AI may interact with:
• Regulatory strategy documents
• Safety case information
• Clinical trial data
• Confidential product development plans
If AI operates outside user-level permission controls, it may inadvertently surface information to unauthorised users. Additionally, when data leaves the core platform for processing, organisations face concerns around intellectual property and privacy.
What You Need: Permission-Aware by Design
With CARA, every AI request is executed within the context of the individual user’s permissions. If a user cannot access a document manually, AI cannot access it on their behalf. Furthermore, AI operates within the CARA environment. Data is not used to train external models across customers.
This approach ensures:
• Protection of proprietary information
• Alignment with internal governance policies
• Reduced risk of unauthorised exposure
Why This Matters
In regulatory inspections, organisations must demonstrate control over information access and system behaviour. AI cannot introduce uncertainty into that control framework. By embedding AI within existing security architecture, CARA ensures innovation does not compromise compliance. CARA AI also doesn’t hallucinate, produces output and answers based on the information already in your system, if it’s not able to give you a good response, it will not. Everything is tracked, and it references which document or folder it got the information from, so you can be sure your information is correct.
For life sciences organisations, that assurance is essential.
