PartiXen

The Secure AI Sandbox

PartiXen is a hardened, isolated execution environment for AI agents. It gives untrusted models a place to think, call tools, and act — without giving them access to anything you haven’t explicitly authorized.

If your AI workload touches sensitive data, runs third-party models, or orchestrates tools that can change real state, it belongs in a sandbox. PartiXen is that sandbox.

Why Sandbox AI?

Modern agents are non-deterministic processes with network access, tool use, and the ability to be prompt-injected into doing something you never intended. Treating them like ordinary applications is a category error.

The risks are concrete:

• Prompt injection turning a helpful assistant into a data exfiltration tool
• Context leakage where sensitive inputs end up in logs, outputs, or downstream prompts
• Tool misuse where an agent invokes an action outside the scope of its task
• Opaque data flow that makes compliance and incident response nearly impossible

PartiXen contains these risks at the infrastructure layer, so a compromised agent cannot compromise the system around it.

What PartiXen Provides

Strong Isolation
Every agent runs in its own sandboxed domain with enforced boundaries between memory, filesystem, network, and tool surfaces. Compromise of one agent does not cascade to the host or to other agents.

Mediated Tool Use
Tools are not invoked directly by the model. Every tool call passes through a policy layer that authorizes, logs, and — where needed — rewrites the request before it reaches the outside world.

Controlled Context Windows
Fine-grained control over exactly what data can enter a model’s context, scoped per agent, per task, and per data classification level.

Output Sanitization
Model outputs are inspected against policy before they reach users, downstream systems, or other agents. PII, classified markings, secrets, and policy violations are caught at the boundary.

Full Data Flow Visibility
Complete, tamper-evident audit trails for every input, tool call, and output. You can answer the question “what did this agent see, and what did it do?” for any point in time.

Policy Enforcement at the OS Layer
Data handling rules live below the application — not in a prompt, not in a wrapper library, not in something an agent can talk its way around.

Why an Operating System, Not a Library

PartiXen isn’t a plugin, SDK, or prompt template. It’s a complete execution substrate for agents:

• Enforces isolation the agent cannot escape
• Mediates every interaction between the model and the outside world
• Runs identically on local hardware, in private cloud, or in air-gapped environments
• Provides APIs for application developers without exposing the enforcement layer to the model

The security guarantees come from where the controls live. A library an agent can call is a library an agent can be tricked into calling incorrectly. An OS the agent runs inside is a boundary the agent cannot cross.

Built for High-Assurance Environments

For defense, intelligence, healthcare, and regulated industries, PartiXen is designed to meet the bar where a data leak is not a bug but an incident:

• No classified or regulated data reaches commercial AI endpoints unless policy permits it
• Strict, auditable control over what information an agent can access
• Evidence-grade logs for compliance, incident response, and accreditation
• Deployment patterns aligned with NIST, FedRAMP, and equivalent frameworks

Use Cases

• Running third-party or open-weight models against sensitive internal data
• Giving agents tool access (code execution, browser use, system commands) without giving them the keys to the environment
• Multi-tenant agent platforms where tenants must remain isolated
• Classified or CUI workloads that need AI capability without AI-shaped data leaks

Ready to put your agents in a real sandbox?
Contact us to discuss PartiXen deployment options.