Productized entry

Secure AI audit

A Secure AI audit is needed when the company already has an AI pilot, RAG, chatbot or the use of external AI services, but there is no confidence in security, data and risk management.

Abstract light hero picture for AI, RAG and corporate LLM systems

Login Format

A Secure AI audit is needed when the company already has an AI pilot, RAG, chatbot or the use of external AI services, but there is no confidence in security, data and risk management.

What's included

Data

What is transmitted to the AI, where requests and responses are stored.

access rights

Roles, administrators, users, sources and rights.

Architecture

Models, RAGs, Integrations, Logs, Loops and Operations.

Risks

PD, trade secret, hallucinations, prompt injection, vendor lock-in.

Artifacts at the output

ArtifactWhy is it needed?
Risk registerPriorities and risks of the AI ​​environment.
Security checklistControl requirements for data, access and logs.
Architecture notesNotes on the current architecture.
Remediation roadmapCorrection and development plan.

Team composition

Frequently asked questions

Is this a model code audit?

No. The main focus is enterprise architecture, data, integrations, access and operation of AI.

Suitable for external AI services?

Yes, if you need to understand what data and processes fall into the external loop.

Can it be combined with a pilot?

Yes, secure audit can go before the pilot or in parallel with him.

Application form

Fill out a short application or send an email to info@restart.re. For the first conversation, it is enough to describe the outline, the role of the organization, current systems, limitations and the desired outcome.

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Let's discuss your environment

Describe the task, current systems, constraints, and expected results. We will offer a practical first step: diagnostics, pilot, audit, roadmap or project team.

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