Model Context Protocol (MCP)
MCP is an open standard that works like a common plug between an AI assistant and your software: CRM, ERP, databases, documents. We build these connections so AI works from your real data, with only the rights you choose to give it.
Secure connector
Reads and writes only what you approve.
Your existing tools
What we do for you
Concrete examples of what AI can do once it is connected to your tools, within the limits you set.
A customer's history
A salesperson asks where things stand with a customer. The assistant checks the CRM and sums up the latest emails, quotes and orders in a few lines.
Stock and lead times
The assistant reads your ERP to answer questions about stock levels, delivery times or an order's status. It looks, it does not change anything.
Searching your documents
Contracts, procedures, product sheets: AI finds the right passage and shows where it came from. Here MCP works together with RAG, a method that fetches the relevant extracts before the answer is written.
Controlled updates
Creating a task, filling in a record, drafting an email: AI writes into your tools only where you allow it, and asks for your approval on sensitive actions.
Your in-house tools
Your internal software or in-house API becomes available to AI through a dedicated MCP server, with no need to rewrite it.
Figures on request
The managing director asks for this month's revenue by branch. The assistant queries the database in read-only mode and replies with the figures and where they come from.
How we work
Four steps, from choosing which tools to connect to everyday use by your team.
AI assessment
We list with you the questions and tasks AI should handle, the tools it needs to read, and the data that must stay out of its reach.
Process redesign
We write down the business context AI needs: your terms, your rules, who is allowed to see what. For each tool we set read-only, write, or human approval before anything happens.
From pilot to rollout
We connect one or two sources first and check the answers on real cases. Each new tool is then added as a separate module, without rebuilding the rest.
Training and governance
We train your team, log every time AI touches your data, and track usage, cost and quality: GDPR, the EU AI Act, access rights reviewed regularly.
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