Local-first architecture
fAIrewall is built around processing on the user's device. Its role is to inspect and minimize sensitive content before submission, instead of routing prompts through a hosted third-party gateway.
Pre-send minimization
The product focuses on reducing exposure before a prompt is sent. That makes minimization the first line of defense, rather than relying only on downstream provider settings or post-submission controls.
Policy-driven protection
Different workflows require different protection levels. fAIrewall is designed to support policy-based behavior so users and teams can align protection with operational needs and risk tolerance.
Local audit visibility
Where audit features are enabled, visibility is designed to stay local and support internal review, accountability, and evidence workflows without turning the product into another cloud logging system.
Stricter behavior when needed
Some environments prioritize convenience. Others require stronger guarantees. fAIrewall is designed to support stricter operational modes when silent fallback is not acceptable.
Consistency across AI tools
Many teams do not use just one AI tool. fAIrewall is designed to bring a more consistent control layer across major AI web apps, reducing fragmentation in everyday usage.
Current provider coverage
Current web support includes ChatGPT, Claude, Gemini, and DeepSeek.
What fAIrewall is not
fAIrewall is not a model provider and not a hosted AI platform. It is a local control layer designed to help reduce sensitive data exposure before prompts are submitted.
Security boundaries
No security product works in isolation. Effective protection still depends on supported environments, correct configuration, and sound user practices. fAIrewall is designed to strengthen control before prompts are sent and to reduce avoidable exposure in real workflows.