AI agents.
Autonomous processes.

What are AI agents?

An AI agent is assigned goals and executes them independently by analyzing data, planning actions, and controlling systems. AI agents use AI models, logic, and context to run multi-step processes without continuous human intervention.

With AI agents, you turn years of organizational and industry knowledge into smart digital workers, for example for:

• Automatically checking, enriching, validating, and forwarding data
• Workflow automation across multiple systems
• Supporting finance, operations, or compliance processes

How can your company benefit from AI agents?

Well-designed AI agents provide direct and structural benefits:

• Time savings: repetitive and time-consuming tasks are fully automated
• Fewer errors: consistent execution without human mistakes
• Lower operational costs: scalable processes without extra capacity
• Faster cycle times: tasks and decisions executed 24/7
• Better focus: employees concentrate on strategic and substantive work

AI agents are particularly suitable for organizations that want to scale without proportional growth in staff.

AI agents connected to your systems

The power of AI agents lies in integration. Fenêtre develops AI agents that work directly with your existing IT landscape and independently perform actions in:

• CRM and ERP systems
• Document management and case management system
• Internal databases and data warehouses
• External APIs and applications

This way, AI agents function as digital colleagues who start workflows, determine next steps, and complete processes.

Read more about custom software and AI

Start smart with AI agents

Would you like to know how AI agents can help your organization work more efficiently and perform better?

With our AI advisory, you quickly discover where the biggest opportunities lie. No-obligation contact, response within 1 working day.

What is your AI challenge?

RAG: AI as your own tool for businesses

Retrieval Augmented Generation (RAG) combines generative AI with your own company data and knowledge sources. The answers from your own sources are verifiable, which can save your employees hours of work per day. Especially for Knowledge Intensive Tasks, this is a solution:

1. The user asks a question in natural language.
2. AI models consult your own documentation, knowledge bases, or databases in real time.
3. RAG provides consistent, verifiable answers in natural language.

RAG is ideal for FAQ systems, customer service, legal or technical support. And thanks to storage in your own location, this use of AI for businesses is safe to deploy. Your company data always remains under your control.

How Retrieval Augmented Generation works

MCP: securely connecting AI to your systems

Model Context Protocol (MCP) ensures that AI models can collaborate in a controlled way with your own systems, applications, and processes. Instead of separate point-to-point integrations, MCP determines which context, data, and actions an AI is allowed to use. This makes AI usable for business-critical tasks without losing control or security.

1. A user or AI agent asks a question or starts an action.
2. The AI model requests access via MCP to specific context or functionality.
3. MCP determines which systems, APIs, or processes are available.
4. The AI performs the task within predefined rights and boundaries.

MCP is ideal for AI agents, process automation, and integrations with systems such as CRM, ERP, or CMS. Because all access is centrally governed, this use of AI is secure, scalable, and fully under your organization’s control.

How the Model Context Protocol works

Proven case studies