Features
Dec 30, 2025
Trust is our priority number 1
Why data protection, privacy, and cybersecurity are now baseline requirements for adopting AI in industrial commercial workflows.
Your data stays within clear trust boundaries
Industrial RFQs, proposals, and technical documentation are among a company’s most sensitive assets. The primary concern customers raise is simple: where does the data go?
In Loonar, the data flow is deliberately constrained. Customer RFQs and internal documents remain inside a defined customer data boundary. Only the minimum necessary portions of your documents are processed to generate an answer, and the full document set never leaves the trusted environment.
Outputs are generated, stored, and reused only inside the customer’s tenant. This design removes ambiguity: data does not drift across systems, accounts, or other customers.
No AI training and no data retention
A second, common concern is how AI providers handle customer data. The answer is direct. Customer data is NEVER used to train AI models, now or in the future.
Prompts and outputs are processed transiently and are not retained by external model providers once a response is generated. There is no human review of customer data and no secondary use for analytics or improvement.
Ownership remains entirely with the customer. This approach avoids hidden trade-offs between convenience and confidentiality and aligns with the expectations of regulated and risk-aware industrial organizations.
Security is built in, not bolted on
Security is not treated as a feature layer added after the fact. Data is encrypted end to end, both in transit and at rest. Each customer operates in a logically isolated tenant, preventing cross-access by design.
Access controls follow least-privilege principles, with clear auditability of who accessed what and when. Backups, disaster recovery, and logging are part of normal operations, not exceptions.
The result is an environment that feels familiar to industrial IT and security teams: predictable, controlled, and aligned with how critical systems are expected to behave.
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