Assistant Privacy Policy

Benched.ai Editorial Team

An assistant privacy policy describes what user data is collected, how it is processed, and under which conditions it is retained or shared. Clear policies build trust and satisfy legal requirements.

Key Policy Sections

Section	Questions Answered	Typical Content
Data Collected	What fields?	Prompts, usage metadata, IP address
Purpose	Why is data needed?	Model improvement, billing, abuse detection
Retention	How long kept?	30 days raw, 2 years aggregates
Sharing	With whom?	Sub-processors, research partners
User Controls	How to opt-out / delete?	Dashboard delete button, GDPR export

Comparison of Retention Defaults (2025)

Provider	Raw Prompt Retention	Aggregated Logs
OpenAI	30 days	1 year
Anthropic	90 days	2 years
Google	6 months	18 months

Design Trade-offs

Longer retention aids debugging but raises breach impact.
Fully deleting prompts breaks reproducibility unless hashed fingerprints stored.
Differential privacy noise degrades analytics accuracy.

Current Trends (2025)

Client-side encryption plugins let enterprises keep prompts encrypted end-to-end.
Regional privacy laws (India DPDP Act) spur geo-fencing of logs.
Privacy policies include LLM-specific clauses such as "models will not train on your data unless you opt-in."

Implementation Tips

Pin privacy policy version to each API response header for audit traceability.
Provide a machine-readable JSON of policy metadata to power automated compliance scanners.
Regularly review third-party sub-processor contracts for scope creep.