AI Security

• Data

  What goes into the AI and where it ends up. Who can see it, where prompts and responses are stored.

• Access and actions

  Which systems the AI is connected to and what it can do on its own: send emails, change data, create orders, make payments.

• Resistance to manipulation

  Whether text in a chat, email, website or document can make the AI act differently than you intended. This is called prompt injection.

• Rules and accountability

  Who is responsible for AI answers, which services employees may use and which data must not be entered there.

1. 01

   AI Systems & Agents Inventory

   What it is

   An inventory and review of all artificial intelligence systems, bots and assistants used in the company, including those management does not know about.

   What we do

   We find out which AI systems and bots you have, what data they receive, what they are connected to and what they can do.

   Result

   Know exactly where AI works in your business.

   Get a complete map of your AI systems and a prioritized list of hidden security risks.

2. 02

   Context Boundaries & Permission Levels

   What it is

   Setting access boundaries and permissions for AI systems so they do not have excessive rights.

   What we do

   We define what the AI sees (context), what it can do on its own and what only after a person confirms. We set access boundaries for AI systems, agents and applications.

   Result

   Keep AI under control.

   Reduce the risk of a bot taking actions or making decisions without your knowledge.

3. 03

   Data Protection When Using AI

   What it is

   Control over which corporate and client data goes to external language models and where conversations are stored.

   What we do

   We decide which data can be sent to which services, how to hide what is not needed and where prompts and responses are stored.

   Result

   Protect client data and trade secrets.

   Reduce the risk of leaks through public AI services.

4. 04

   Employee AI Usage Rules & Policy

   What it is

   An internal policy for the safe use of artificial intelligence in your team's daily work.

   What we do

   We prepare clear rules: which services are allowed, which data must not be entered, who is responsible for the result. If needed, we train your team.

   Result

   Give your team clear guidelines.

   Employees will know which tools are safe to use and what puts data at risk of leaking.

5. 05

   Protection Against Prompt Injection and Jailbreaks

   What it is

   Testing how well AI bots and agents resist manipulation through text instructions (so-called prompt injection).

   What we do

   We check whether text in a chat, email or document can make your bot or agent reveal too much or carry out someone else's command.

   Result

   Protect your bots from attackers.

   Find out whether your AI can be tricked into giving discounts, revealing confidential data or bypassing business logic, and close those weak spots.

We assess the settings, access and processes around AI. We do not build or train AI models, and we do not examine how they work internally.

• Website or messenger chatbotAnswers your clients.Risk: Revealing too much or promising something you never promised.
• Internal document AI assistant (RAG)Answers employees' questions from the company's document base.Risk: Showing a document to someone who should not see it.
• Autonomous AI agent executing API actionsSends emails, issues refunds and updates database records on its own.Risk: Doing something unwanted without your knowledge or on someone else's command.
• Voice bot and call handlingTakes and transcribes client calls.Risk: Call recordings and client data are stored and transferred without protection.
• AI inside your productFeatures built on language models in your app or service.Risk: Leaks of user data and manipulation through what users type in.
• AI automations and workflowsConnected services that call AI on a schedule or when an event occurs.Risk: Access keys inside workflows and permissions that are too broad.
• AI coding assistantsSuggest and write code.Risk: Code and passwords go to an external service, and unsafe solutions end up in the code.
• Employees using public LLMs with company dataEmployees use AI on their own, without the company knowing.Risk: Contracts and client data end up in external services.

1. Step 1Quick consultation

   We learn where and how you use AI and agree on the scope of work.

2. Step 2Map of AI in the company

   We list the AI systems, bots and agents, their data and their access.

3. Step 3Risk assessment

   We check settings and access and look at what could go wrong.

4. Step 4Setting boundaries

   We define contexts, control levels and rules for what the AI does on its own and what only after confirmation.

5. Step 5Report and rules

   We hand over the report, recommendations and rules for employees.

• An internal assistant has access to all company documents

  Limit the AI's access to the data it needs and split permissions by role.

• An employee uploaded a client contract to a public AI chat

  Introduce rules, define which data can be sent to which services, and offer a safe alternative.

• The website bot promised a client a discount that does not exist

  Limit what the bot can promise and add a handoff of complex questions to a person.

• An AI agent can send emails on behalf of the company

  Keep human confirmation for actions that cannot be undone.

Generalized examples of typical situations, not stories of specific clients.

Other services

• Technical Security AuditFind out where you are vulnerable before an incident occurs.
• Security for DevelopersCI/CD pipeline checks, secrets scanning, and environment isolation.
• Risk Reduction during AuditsNIS2 (KSC), ISO 27001, RODO/GDPR, PCI DSS compliance and questionnaire preparation.