One workspace for AI. A local boundary for sensitive data.

Everyday AI

A workspace people can use for real work.

AI adoption spreads through writing, analysis, research, document work, summaries, and internal problem-solving. A shared workspace makes approved models easier to access and gives the organization a consistent place to apply protection.

Employees do not need to manually identify every supported sensitive value before each request. Sano’s local protection layer is designed to make that boundary part of the workflow.

• Access to leading proprietary and open models
• German and English working contexts
• A consistent protection experience
• Designed for desktop-based knowledge work

Local first

Protection before the model—not after exposure.

Detection and replacement happen on the user’s device before the prompt is sent. The external model works with placeholders and surrounding context rather than the original protected values.

This architecture reduces reliance on a central service holding both the protected mapping and the user’s raw context. Restoration can happen where the authorized user already works.

• On-device privacy processing
• Protected prompts before model inference
• Local restoration of authorized context
• No need for Sano to centrally store original values

Choice of models

Use the right model without redesigning the privacy boundary.

Different tasks benefit from different models. Sano Work is designed to give users access to a selection of leading providers and open models through one protected experience.

The local protection concept sits before the selected model. This separates the sensitive-data boundary from the choice of model and gives organizations more flexibility as capabilities, policies, and provider requirements evolve.

• Model choice based on task requirements
• One interface across supported providers
• A provider-independent protection step
• Room for future model and API options

Privacy built into the interaction.

01 · Write naturally

The user works with the context needed for the task instead of manually rewriting every prompt.

02 · Protect locally

Supported sensitive values are detected and replaced on the device before the request leaves.

03 · Use the answer

The selected model responds and the protected context is restored locally for the authorized user.

Privacy-first workspace questions

What types of work can teams do in Sano Work?

The workspace is designed for common language-model tasks such as drafting, analysis, summarization, research, and document-related work. Exact features and provider availability may change as the product develops.

Where does the sensitive-data detection run?

The product is designed so supported sensitive-data detection, replacement, and restoration run locally on the user’s device before and after the external model request.

Is Sano Work available now?

Sano Work is currently inviting organizations to request early access. Contact the team to discuss requirements, rollout context, and availability.

Go deeper into secure AI

Secure AI for Enterprise

A practical approach to protected AI adoption across European organizations.

AI Data Protection

Understand the local protection step before a model request.

Bring privacy-first AI into everyday work.

Request early access and tell us which teams and sensitive workflows you want to support safely.