cross-provider protection
Gemini
Copilot
Ollama
Claude
OpenAI
Mistral
The Rest...
Why Patronus?
Patronus combines endpoint-level observability, local-first protection, and a practical route from monitoring to stronger controls as AI usage spreads across the organization.
See AI activity as it happens
Patronus monitors prompts, responses, and model traffic directly on the endpoint. This gives teams visibility into how AI tools, browser extensions, local models, and provider APIs are actually used in day-to-day workflows.
Control what AI is allowed to access
Patronus helps enforce guardrails around sensitive data, risky prompts, and unauthorized usage. With local policy enforcement, teams can define what AIs are allowed and what tools, agents, and models are permitted to send, access, or execute.
Reduce AI risk before it becomes exposure
Patronus reduces the risk of data leakage, prompt injection, and uncontrolled AI behavior without adding another cloud dependency. Protection happens where the interaction starts: on the device.
How Patronus works ?
Patronus starts with the foundation most teams are missing today: visibility. From there, protection, policy, and governance become much easier to implement with confidence.
On-Device AI Firewall
Instead of relying on multiple tools, integrations, or extensions, Patronus is designed as an AI firewall operating in the network path on the endpoint.
Our novel detection mechanism identifies AI traffic in one-digit milliseconds and allows us to detect AI interaction across apps, browsers, and providers.
On-Device Protection
Nobody likes another cloud dependency, especially when dealing with sensitive data, which is common in AI systems.
Cloud compute enables fast detection, but comes at the cost of privacy and doesn’t always deliver the best performance.
At Patronus, we design and build our own AI systems to run directly on-device, in real time.
Our methods achieve state-of-the-art performance, competing with LLM-based solutions at a fraction of the cost.
Assess your AI Act readiness.
23 questions derived from the original text of Regulation (EU) 2024/1689, focused on the technical and organizational obligations applicable to deployers. The output is a personalized PDF report with sub-scores per dimension and prioritized findings.
For who is Patronus ?
Patronus protects AI interactions at the endpoint. The value looks different depending on whether you own security, build with models every day, roll AI out across a company, or use AI privately.
Our pillars of AI security
Observability
Any protection starts with observability.
We see what you don’t.
Zero-Trust
AI operates across apps, tools, and hidden layers.
We trust no interaction by default.
Protection
Real security goes beyond detection.
Stopping threats requires real-time enforcement.
We keep the human-in-the-loop.
Privacy-by-Design
Built offline-first to protect your data.
We keep your data on your device*.
*Only minimal, compliance-ready metadata ever leaves your device on your demand.
The Roadmap
From monitoring to full AI protection - shipped in three focused phases.
In Development
Q2 2026
Phase 1
Monitoring
Initial core release with foundational monitoring
and assessment capabilities.
Real-time protection available in early alpha.
Enforce company policies consistently across
providers and applications.
Planned
Q3 2026
Phase 2
Protection
Planned
Q4 2026
Phase 3
Integration
Seamless integration into your existing security stack.
Integrate Patronus on your mobile devices.
>>
What teams demand
Ship AI features fast, without bottlenecks
Use any LLM or agent without restrictions
Integrate cloud AI into every workflow
Automate tasks with minimal IT overhead
VS
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What security requires
Full audit logs and data traceability
Zero data leakage to external services
Strict access control and policy enforcement
GDPR, SOC2, and regulatory compliance
Patronus resolves the tradeoff
Deploy AI at full speed — with full security, full privacy, and zero compromise.
FAQ
What is an AI Firewall?
An AI Firewall is a security layer that monitors, analyzes, and controls interactions with AI systems in real time. It sits directly on the endpoint (your device) and inspects AI-related traffic—such as prompts, responses, and tool usage—before data leaves the device. Similar to how antivirus software protects against malware, an AI Firewall protects against risks like prompt injection, sensitive data leakage, and unauthorized AI usage.
Do you depend on the cloud?
No. Core protection runs entirely on-device. Patronus Protect is designed with a local-first architecture, meaning all detection and enforcement decisions happen directly on the endpoint. This ensures: No dependency on external services for real-time protection Low latency and immediate enforcement Strong privacy guarantees Optional cloud features (e.g., dashboards or compliance insights) can be enabled, but are not required.
How can this run in real time on the endpoint?
We use a multi-layer detection pipeline optimized for performance: Lightweight heuristics and classifiers handle the majority of traffic instantly More advanced models are only used when needed Streaming-aware processing allows decisions even during partial responses (e.g. WebSockets) This approach avoids constant heavy computation while still maintaining high detection accuracy.
Do you collect my data?
No. All analysis happens locally on your device. We do not store or send prompts, responses, or sensitive content to external servers. If cloud features are enabled, only minimal metadata may be shared, such as: Usage patterns (e.g., which AI tools are used) Risk scores and categories Performance metrics Sensitive content is never transmitted.
Why should I protect local LLMs?
Local models are not inherently safe. Even when running on-device, they can: Access sensitive files or system data Execute tools or commands (e.g., via agents or MCP integrations) Be manipulated through prompt injection or malicious inputs Without controls, a local LLM can still leak data, perform unintended actions, or be exploited. An AI Firewall ensures that every interaction—local or cloud—is governed, monitored, and enforceable.
