Working responsibly and practically with AI at the Amsterdamse Federatie van Woningcorporaties
Amsterdamse Federatie van Woningcorporaties
DSL Managed Data Platform
A managed data platform as the foundation for data and AI.
Bring data from different systems together without having to build an entire data team yourself.
Trusted by leading organisations
Why we built this,
Business data is often spread across ERP, CRM, financial and operational systems. As a result, reporting takes a lot of manual work, and departments do not always use the same figures.
A central data platform can solve this, but building it is only the first step. Data sources change, integrations need to keep working, and data quality needs to be monitored. That requires ongoing technical management.
With the DSL Managed Dataplatform, we bring data from different systems together in one managed environment. This creates a reliable foundation for dashboards, analyses and AI applications.
Our approach,
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Start with a specific application
We first determine which report, analysis or AI application needs the platform. We then map the relevant data sources and definitions.
This way, we build a foundation that is used from the outset, rather than a broad platform with no clear application. -
Set up the platform and data flows
We set up the environment and build the data flows that process information from the selected systems. We take data quality, access management and future expansion into account.
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Manage and expand where needed
Once the platform is in use, we continue to monitor and maintain it. When systems or information needs change, the environment can be adapted accordingly.
New data sources, dashboards, analyses and AI applications can then be added on the same foundation.
Three starter packages
Packages,
€1750 per month*
Data ready
Up to 2 connectors
Medallion architecture
Dashboard
One-off set-up costs of 10k euros
€1900 per month*
Data smart
Up to 2 connectors
Medallion architecture + feature table
AI/ML model
Model serving
One-off set-up costs of 15k
€2100 per month*
Data intelligent
Up to 2 connectors
Data intelligence (Genie)
Run your own queries, create dashboards in no time and talk to your data in plain language.
One-off set-up costs of 20k
*Azure consumption is billed separately to the client
Get started quickly, with no large upfront costs, for a fixed monthly price
The platform grows with your organisation: you add new data sources, dashboards and AI applications, let employees query data themselves using SQL or a Genie agent, and expand with other agents, for example for customer service.
What we've built before,
Three projects from our work with data and AI.
Further reading
Blogs and in-depth articles from our team.
24 Aug 2026
Three lessons from our AI projects
What we learned from dozens of AI projects: start with the decision, treat data quality as an organisational issue and arrange management in advance.
18 Aug 2026
From pilot to production: why most AI projects stall
Most AI projects stall not because of the technology, but because of data, teams and processes. Read what it takes to move from pilot to production.
25 Jun 2026
Responsible AI: from principles to practice
AI is developing rapidly. New models emerge almost every week, and more and more organisations are experimenting with AI.
Get in touch
Stef Stoelwinder
Business DevelopmentE-mail info@datasciencelab.nl
Phone +31 (0)20 3636 724
Frequently asked questions,
The platform is suitable for organisations that want to use data from multiple systems for reporting, analysis or AI, but do not have all the necessary technical expertise in-house. The exact setup depends on the data sources, the existing environment and the applications the organisation wants to start with.
No. We prefer to start with the sources needed for one specific application. This keeps the initial setup manageable and provides a usable foundation sooner. Other systems and applications can be connected to the same platform later.
DSL can manage the technical side of the data platform and data flows. This may include monitoring, maintenance and support with changes. We agree in advance exactly which tasks are included in the service.
Storing data does not automatically make it usable. A data platform must process data, maintain consistent definitions and make information available reliably. Access control, monitoring and responsibilities also need to be put in place. Only then does the platform provide a usable foundation for data and AI.
Not every AI application requires an extensive data platform from the outset. Every application does, however, need reliable, accessible data. By starting with one specific application, we can determine the technical foundation it needs and avoid building a larger platform than necessary.