Connecting systems: the indispensable foundation for data and AI in SMEs

Key Takeaways: The average SME quickly ends up running on eight to fifteen separate software packages: CRM, ERP, webshop, accounting, email marketing, inventory. These rarely talk to each other, which means customer and revenue figures differ from system to system and no one has a complete picture. This is the biggest barrier to AI and data-driven management. A single connection costs from a few thousand euros, an iPaaS tool like Make or Zapier 20 to 200 euros per month, and a central data platform between 20,000 and 60,000 euros. The payback period is often between six and eighteen months, mainly through saved hours of manual work and fewer errors. Connect first, then do AI.

The silent problem: systems that don't talk to each other

Ask an SME owner how many customers they have, and you'll get three different answers depending on which system you consult. The CRM counts 4,200 contacts, the accounting system knows 1,800 invoicing customers, and the webshop has 6,500 accounts. Which number is correct? No one knows for sure. This isn't an exception but the norm. In recent years most companies have switched, one by one, to specialized SaaS packages, each excellent at its own task, but standing as separate islands with no connection between them.

The result is duplicated work and silent errors. A salesperson updates an address in the CRM, but accounting still sends the invoice to the old address. A product is sold out in the webshop but still listed as in stock in the ERP. Employees export Excel files every day, copy columns across, and email versions back and forth. Research estimates that knowledge workers spend up to 20 percent of their time searching for and combining data that should actually align automatically.

This is exactly why AI disappoints in many SMEs. You can build the smartest model imaginable, but if the underlying data is fragmented and contradictory, you'll get unreliable outcomes. An AI-ready data foundation doesn't start with an algorithm, but with simply making your existing systems work together. Without that basis, every investment in AI is built on quicksand.

What data integration is: APIs, iPaaS, and custom development

Data integration means that data flows automatically and reliably between systems, so it is correct everywhere. There are broadly three technical routes for this, increasing in power and cost.

The most direct form is an API connection: almost every modern software package has an API, a kind of digital power strip that lets other systems retrieve and write data. Connecting two systems directly via their APIs is often the fastest solution for a well-defined problem, for example automatically posting webshop orders into the accounting system. Such a single connection typically costs from a few thousand euros, depending on the complexity and how well the APIs are documented.

Above that sits iPaaS (integration platform as a service), tools like Make and Zapier. These are visual platforms that let you stitch together hundreds of SaaS tools without much programming, using ready-made building blocks. You drag a trigger ("new lead in form") to an action ("add to CRM and send a welcome email"). Costs range from around 20 euros per month for light automation to 200 euros or more at higher volumes. Ideal for getting started quickly, but less suited to heavy data processing.

The most durable route is a custom data pipeline to a central data platform: an environment where all sources come together, are cleaned up, and become available as a single reliable source for reporting and AI. This is bespoke engineering, with the most control and the best scalability, but also the largest investment. For SMEs such a platform typically ranges between 20,000 and 60,000 euros, plus 100 to 500 euros per month in hosting. We previously wrote in detail about the cost of an ETL pipeline for SMEs.

When do you choose which approach?

The biggest pitfall is overengineering: building an expensive data platform for a problem that a 30-euro-per-month Zapier flow would have solved. Just as often the opposite happens, where a company keeps muddling along for years with fragile Make scenarios while the volume has long called for a real pipeline. The art is in choosing the right approach for the right situation.

Choose iPaaS (Make or Zapier) when you want to connect a handful of popular SaaS tools, the data volume is modest (tens to a few hundred records per day), the logic is relatively simple, and you want quick results without a developer. A marketing team that wants to send leads from LinkedIn ads to HubSpot and get a Slack notification for each request fits perfectly here. Expect a few days of work and a low monthly cost. The limit comes into view with large volumes, complicated transformations, or strict reliability requirements, because iPaaS flows break silently and are hard to debug.

Choose a direct API connection when you want to connect exactly two systems at a specific point and the standard connectors fall short. Think of an industry-specific ERP without a ready-made Zapier integration. This is targeted custom work: from a few thousand euros, ready within one to three weeks.

Choose a central data platform as soon as you want to combine more than four or five sources, analyze historical data, need reliable dashboards for data-driven decision-making, or seriously move toward AI. A wholesaler that wants to bring together inventory, purchasing, sales, and marketing to forecast demand cannot avoid a real pipeline. The investment of 20,000 to 60,000 euros typically pays for itself within six to eighteen months, mainly through saved manual work, fewer errors, and better decisions.

Cost, payback period, and the WBSO

Let's be honest about money, because non-committal promises help no one. A realistic path for an SME moving from separate systems to a connected whole often looks like this: one to three critical connections first (together 5,000 to 15,000 euros), followed by a central platform in a second phase (20,000 to 60,000 euros). The monthly costs stay limited: hosting of 100 to 500 euros plus any iPaaS licenses.

The payback comes from three sources. First, saved hours: an employee who spent an hour and a half each day on manual re-typing and exporting quickly delivers 8,000 to 12,000 euros per year in reclaimed time. Second, fewer errors: an incorrectly sent invoice or a lost order due to conflicting stock costs money and goodwill directly. Third, and most important in the long run: better decisions because you finally steer on reliable figures. And don't forget that clean, connected data also lays the basis for later data quality improvements.

An underrated advantage: developing connections and data pipelines often qualifies as technical-scientific work and therefore falls under the WBSO scheme. This significantly lowers the wage costs of the development hours, sometimes by as much as a third of the development portion. That noticeably shortens the payback period and makes the difference between a hesitant and a decisive decision. It pays to factor this into the business case in advance.

Stratalytic and data integration

We help SMEs turn their separate systems into a reliable foundation, without unnecessary complexity or vendor lock-in. Our approach:

• We first map your system landscape and determine which connections deliver the most value, so you don't have to build the heaviest platform right away.
• We choose pragmatically: iPaaS where that suffices, custom pipelines where needed, always based on your volume and requirements.
• We build a central data platform that grows with you and immediately delivers usable dashboards for management.
• We lay the groundwork for future AI applications right away, whether that's AI agents, smarter marketing, or churn prediction.
• Where possible we leverage the WBSO to significantly reduce your investment.

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Frequently asked questions

What exactly is data integration?

Data integration means making separate systems such as CRM, ERP, webshop, and accounting work together, so the same data is correct everywhere and flows through automatically. This can be done through ready-made API connections, an iPaaS tool like Make or Zapier, or custom pipelines to a central data platform. The goal: a reliable, complete picture of your business.

What does connecting systems cost for an SME?

A single connection between two systems often starts from a few thousand euros. An iPaaS subscription (Make, Zapier) costs roughly 20 to 200 euros per month. A full central data platform with multiple sources typically ranges between 20,000 and 60,000 euros one-time, plus hosting of 100 to 500 euros per month. The right choice depends on your data volume and the number of systems.

When is Make or Zapier enough and when do I need custom development?

Make and Zapier are ideal for simple automations between popular SaaS tools with limited data volume, such as sending a lead from a form to your CRM. As soon as you process large volumes, need complex transformations, want to analyze historical data, or have strict reliability requirements, a custom pipeline to a data platform is the smarter and ultimately cheaper choice.

Why is data integration necessary before AI delivers anything?

AI models and agents are only as good as the data that feeds them. If customer data differs across four systems and no one knows which version is correct, AI produces unreliable outcomes. Connecting your systems first and getting your data in order delivers better insight right away, and only then makes later AI applications truly worthwhile.