Your AI Is Only as Good as Your Data

Everyone is building AI. Every accounting firm, every PE fund, every bank has a project running. Scoring models, prospecting tools, automated analyses. The models are getting smarter, faster and cheaper, and that is precisely the problem. Because when everyone has access to the same models, the models stop being the differentiator. So ask the follow-up question: where does the data come from that feeds those models?

For most organisations, the answer is uncomfortable. A monthly Excel export. A manual copy-paste from annual accounts. Fragments of internal client data. A data provider that "estimates" revenue based on the number of employees found on LinkedIn.

What's actually missing? High-quality, standardised, bottom-up market data.

And you don't close a deal based on estimates. You don't write a risk score. You don't sign off on a dossier.

The problem is not the model

Because the data layer is too weak. According to McKinsey's 2024 State of AI report, poor data quality remains the single most cited barrier to AI deployment at scale in enterprise settings. Not model complexity. Not compute. Data.

A PE fund we work with put it sharply: in a world where AI is commoditised, data quality is no longer a commodity. It is a must. Whoever has the best data wins. Not whoever has the best model.

That is exactly the shift we are seeing. More and more organisations no longer want to view company data in a platform. They want to pull it in. Into their own CRM. Their own ERP. Their own scoring models. Their own source of truth. Via API or recurrent data files.

What makes us different

Not every API is built to feed internal systems. Most data providers in the market work top-down. They scrape websites, estimate revenue, approximate company data. Hover over a number and you will see: "estimated".

openthebox works fundamentally differently.

• Real data, not estimates: What has been filed with the National Bank, published in the Belgian Official Gazette, registered with the Crossroads Bank for Enterprises. Official sources, structured and normalised. Machine-readable. Ready as input, not as an approximation.
• Bottom-up, full market coverage: 2.1 million active Belgian companies, 2.6 million Dutch companies, 5.5 million in the United Kingdom. Not just the usual suspects, but the entire market. Including the companies that never make the papers but generate €3 million in EBITDA.
• 15 years of historical depth: A single snapshot tells you nothing. Trends, evolutions, anomalies: that is where the real insight sits. That requires year-on-year data over a long period.
• Real-time via webhooks: Changes in filings, mandates or corporate structures flow automatically into the connected system. No polling. No delay. Data that lags by days is a risk, not a feature.
• REST API and recurrent data files: Not a lookup tool for occasional use, but an infrastructure layer designed to feed internal systems continuously. Via API for real-time integration, or via scheduled data files for batch processing. Built for integration, not for demos.

And then there is the platform layer. Spiderwebs that map ownership structures. Quick market scans. Consolidated financials. Readiness-to-Sell signals. Context that a purely numerical feed cannot provide. Many clients combine API integration with platform access for exactly that reason.

What this looks like in practice

VGD, one of the largest Belgian accounting and advisory groups, built a custom backend that imports company data via our API and connects it to their internal software. 400+ employees, data flowing automatically into the right files. No manual entry.

But it goes broader. PE funds integrate our data into dealflow systems, proprietary dashboards and LBO models to screen targets faster. Some use the data for hyper-personalised outreach to potential acquisition targets, with concrete numbers on margins, growth and structure. Real estate firms automate portfolio monitoring. Accounting firms accelerate KYC processes.

And it is not just end clients. Technical implementation partners such as Dataroots and Peliqan build the bridge between our API and their clients' internal systems. They are often our first point of contact in these projects.

Not a one-size-fits-all

Every integration is different. A PE fund screening targets needs different parameters than a bank automating KYC. That is why we do not apply a rigid pricing model.

We adapt pricing to the specific use case and let it grow with the project. Because we have a vested interest in the integration succeeding, not in it stopping after three months because the budget ran out.

We work through the architecture, the data flows and the fit with your existing stack from the first conversation. Not as a supplier, but as a partner.

The Window is Closing

The data you need to analyse, score and monitor companies is publicly available. But publicly available and usable are two fundamentally different things.

AI is getting cheaper. Models are getting smarter. But the quality of the output will always be determined by the quality of the input.

Your competitors are not waiting to figure this out. The question worth asking is how far along they already are.

➡️ Take a look on your own, or get in touch for a technical walkthrough of our API and data delivery options.