Connecting AI to your systems
AI becomes useful only once it can see your data and do something with it. This is the connective part. (Technically: MCP — Model Context Protocol, API and SDK integrations.)
When companies call us
- The model answers nicely but knows nothing about your customers, stock or orders.
- Every tool has its own integration and maintenance has got out of hand.
- You want an AI feature inside the mobile app, not another browser tab.
- An internal API exists, but nobody knows how to expose it to a model safely.
In 2026 the Model Context Protocol became the standard for connecting AI to tools — roughly what USB was for peripherals. Instead of a bespoke integration per model and per tool, you build one MCP server and every model uses it.
Hundreds of ready-made MCP servers exist: GitHub, Linear, Notion, Slack, Salesforce, HubSpot, Zendesk, Jira, Confluence, Google Drive, S3, PostgreSQL, Snowflake, Stripe. We connect what can be connected and build a custom MCP server for your internal systems.
The other half of this service is AI inside the product itself — in a mobile app or on the web. Here we build on what we have been doing for years: apps that work outside the demo environment too.
How we work
1. Map the systems and permissions
What AI may see, what it may change and what it must never touch. This is settled before the code, not after an incident.
2. Ready-made MCP servers where they suffice
We will not bill you for building what already exists and is battle-tested. We write custom code only where it adds value.
3. A custom MCP server for your systems
For internal APIs and databases we build a server with clearly bounded tools, input validation and logging.
4. Integration into the product
If the AI feature is to live in an app or on the web, we also handle UX, response streaming, offline states and token cost.
What you get
- A working connection between AI and your systems via MCP or API.
- A custom MCP server for internal systems — with documented tools and permissions.
- A security model: what AI may read, what it may change, and what requires human confirmation.
- AI features inside your mobile app or website, including UX and failure states.
- A view of token costs with limits in place so the bill does not surprise you.
Indicative scope
- Connecting to ready-made MCP servers
- €900 – €2,500
- Custom MCP server (one system)
- €2,500 – €6,000
- AI feature in a mobile app or website
- from €4,500
- Integration maintenance and updates
- from €290 / month
Prices are indicative and exclude VAT. The quality of your internal API documentation affects the price most.
Frequently asked questions
What is MCP and why should I care?
The Model Context Protocol is an open standard for connecting AI to tools and data. In practice it means you build an integration once and use it with any model that supports MCP — which today means practically every major one.
Will we end up locked into one model provider?
That is precisely why we build on MCP and an abstraction layer above the model. Switching providers then becomes a configuration change plus re-evaluation, not a rewrite of your integrations.
Can AI accidentally delete something or email a customer?
Only if you let it. Tools are defined explicitly and outward-facing operations sit behind human confirmation by default. That is a deliberate setting, not a technical limitation.
Can you connect a legacy system with no API?
Usually yes — through the database, exports or a thin middle layer. We assess it in the first phase and tell you what is realistic and what would cost more than it returns.
Integration is usually what decides whether AI ends up as a toy or a tool inside a company.