Secure Private AI Environments

Run AI on Your Data—Without Exposing It to External Models

As organizations adopt AI, one of the biggest challenges is balancing innovation with data security. Sending sensitive data to external models introduces risk—from data leakage to compliance violations and loss of intellectual property.

Kasm Workspaces enables organizations to run private AI models and AI-assisted workflows inside secure, isolated environments, ensuring that data never leaves controlled boundaries.

The Growing Need for Private, Controlled AI

Modern AI adoption introduces two major risks:

1. Sensitive Data Exposure to External Models
Public AI services often require sending data outside the organization, creating risks such as:

Leakage of proprietary data or source code

Exposure of regulated or confidential information

Loss of control over how data is stored or reused

2. Lack of Control Over AI Behavior
Without proper safeguards:

Prompt injection attacks can manipulate model behavior

AI outputs can be exfiltrated without visibility

Autonomous actions can occur without oversight

Organizations need a way to bring AI to their data—not send data to AI.

Run AI Privately, With Security by Design

Kasm enables organizations to deploy AI-ready workspaces where:

Large language models run inside the environment

Privately fine-tuned models are fully contained

Retrieval-Augmented Generation (RAG) connects AI to internal data securely

These environments act as a sandbox for both models & data, enabling powerful AI use cases like:

AI copilots

AI-assisted coding

Data analysis and research workflows

All while maintaining strict control over data flow and execution.

Key Benefits

Complete Data Isolation

All prompts, outputs, and data interactions stay inside the workspace—nothing is sent to external services unless explicitly allowed.

Private Model Execution

Run open-source or fine-tuned models (e.g., Llama-based models) entirely within your environment for full control and privacy.

Secure RAG Architecture

Connect AI to internal knowledge bases using RAG while keeping sensitive data fully contained and governed.

Human-in-the-Loop Control

Prevent autonomous or unsafe actions by ensuring users remain in control of AI-assisted workflows.

Protection Against Prompt Injection

Detect and control malicious inputs and outputs using integrated guardrails and policy enforcement.

Secure Private AI Use Cases

Secure AI-Assisted Development

Enable developers to use AI coding tools while ensuring source code, tokens, and intellectual property never leave the environment.

Private Data Analysis and Research

Allow data scientists and analysts to run AI on sensitive datasets without exposing data externally.

Enterprise AI
Copilots

Deploy internal AI assistants connected to proprietary knowledge bases without risk of data leakage.

Controlled AI
Experimentation

Provide sandboxed environments for testing models, prompts, and workflows safely before production use.

How It Works

A user launches an AI-enabled workspace

A secure, containerized environment is provisioned

Private or open-source models run inside the workspace

Data is accessed via secure RAG pipelines inside the environment

All inputs and outputs are monitored and controlled

When the session ends, the environment can be destroyed with no residual data

Built for Secure, Scalable Private AI

Kasm’s architecture enables private AI at scale:

Core Differentiators

Container-Based Isolation

All AI execution occurs inside ephemeral containers, preventing persistence of risk

Input and Output Control (LLM Guardrails)

Scan and control prompts and responses to prevent data leakage or manipulation

No Endpoint Risk

Even if a user device is compromised, data and models remain protected inside the workspace

Workspace-Based AI Delivery (Not Just Web UI)

Unlike competitors that rely on browser interfaces or extensions, Kasm delivers full environments with complete control

AI Workspace Registry

Prebuilt environments with private models and tools ready to deploy instantly

Flexible Deployment

Run on-prem, in cloud, or hybrid environments to meet compliance requirements

Cost and Operational Advantages

Reduced AI Usage Costs

Control token consumption with session limits and policies
Avoid runaway usage from unmanaged AI tools

Lower Infrastructure Overhead

Replace multiple endpoint security tools with built-in workspace controls
Simplify AI environment setup with preconfigured workspaces

Efficient Compute Utilization

Run workloads on optimized CPU environments (e.g., Ampere) to reduce GPU dependency
Share infrastructure across users and workloads

Industry Applications

Government, Defense & Intelligence

Run AI on classified or sensitive data while maintaining strict control over data sovereignty and preventing external exposure.

Healthcare

Enable AI-driven insights on patient data while ensuring PHI remains protected and compliant with regulatory requirements.

Financial Services

Leverage AI for analysis and automation while safeguarding financial data and maintaining compliance.

Education

Provide secure AI environments for research and learning without exposing institutional or student data.

Energy & Industrial Applications

Analyze operational and infrastructure data with AI while isolating critical systems and preventing external access.

Retail & Manufacturing

Use AI for supply chain optimization, forecasting, and analytics while protecting proprietary and customer data.

The Kasm
Workspaces Platform

Secure private AI environments are powered by the Kasm Workspaces platform—a container streaming solution that delivers secure access to applications, data, and AI workloads through the browser.

Learn more about the Kasm Workspaces Platform

Explore Other Kasm Use Cases

Web Research

Browser Isolation

App Streaming

Remote Workspaces

IoT/OT

Agentic AI Tools

Bring AI to Your Data—Securely

AI adoption doesn’t have to come at the cost of security.

With Kasm Workspaces, organizations can run powerful AI workloads entirely inside controlled environments—protecting data, credentials, and intellectual property while enabling innovation.