System integration via API or middleware, without the retyping.

System integration means that software exchanges data automatically, so you do not have to enter the same information into several packages. Think of an order from your online shop that appears in your accounting and planning by itself, or a lead that reaches your CRM without an export. This usually happens through an API: a fixed entry point that a system opens up to other software.

Middleware is software that sits between your systems and translates, checks and passes on data, so applications work together without every system needing its own integration with every other system. An order from the online shop then travels through that middle layer to accounting, planning and CRM. The middleware records what was exchanged and catches errors when a system is briefly unavailable. It can be an iPaaS in the cloud or a dedicated integration layer.

An iPaaS (integration platform as a service) is middleware delivered as a cloud service: an integration platform with ready-made connectors that lets you set up integrations without programming everything yourself. You usually pay a subscription that grows with usage. Zapier and Make are lightweight iPaaS platforms: fine for simple, standalone steps, but an API change in one of the systems can quietly stop a flow.

If you connect two systems, a direct API integration is usually enough. An iPaaS fits when you mainly connect standard systems, the logic is simple and you want to start quickly. A dedicated integration layer fits once it involves a lot of data, exceptions, your own controls, security or business-critical processes, or when the integrations need to become the foundation for AI. Then you keep the logic and the data fully in your own hands. For each situation we choose what lasts longest.

That depends on the number of systems, the quality of their APIs, how much data flows and how quickly it needs to update. A single integration between two systems with good APIs is a contained project, an integration layer under five systems is a larger one. We always work with a fixed scope and a fixed price agreed up front. Book an intro call for an estimate for your situation.

Yes. AFAS, Exact Online and Moneybird are Dutch accounting and ERP packages, and all three offer a standard API, so integrations with them are straightforward to build. Think of customer data that stays in sync between your CRM and your accounting, or revenue, hours and customer value in one overview without an export. For EVOKE we built a finance platform on an integration with AFAS, with one data layer and controls down to individual transactions.

In principle anything with an API or a reliable export: accounting software such as AFAS, Exact Online and Moneybird, CRM systems such as HubSpot and Tribe, Google Workspace and Outlook, planning, time tracking, online shops and industry-specific software. Examples from our cases: WhatsApp through the Bird API into Tribe CRM, prospects automatically into HubSpot and a finance platform on AFAS.

Then we find a pragmatic route: a scheduled export and import, an integration at database level or software that carries out the actions in the system itself. At In het Veld, FacilityApps did not (yet) have a public API. There, AI prepares everything and an employee checks the outcome before it is processed. What matters is that the solution stays reliable when the system changes.

An integration between two systems with good APIs is often live within a few weeks. We build an integration layer under several systems in phases, and each phase already delivers something. We start with the data flow that currently costs the most time or causes the most errors.

An integration only gets access to the data it needs, with separate keys per system and a log of what is exchanged. If personal data passes through, we record that in a data processing agreement and choose hosting within the EU wherever possible.

A lot. An AI agent or AI assistant is only useful when it can reach your customer, order and financial data. Integrations are therefore the foundation under every serious AI application. Once your systems are connected, you can build an AI Operating System on top, step by step: one layer that understands your data and takes over work.