Bespoke applications built on trustworthy data
We build applications, integrations and data environments where standard products fall short. We combine custom development, master data management and a data layer that supports analytics, automation and AI.
We help organise master data using SNOK MDM, and we work with technologies including Microsoft Azure, SAP BTP, Google Cloud, Snowflake, Microsoft Fabric and Databricks.
Key areas of support
We support organisations across three areas that determine the effectiveness of applications and the reliability of data: organising master data and analytics, building cloud, integration and SAP extensions, and creating bespoke applications for specific business processes.
Data, MDM and analytics
Trustworthy data underpins reporting, automation and the use of AI. We help organise master data, build a consistent analytics layer, and prepare the organisation to work with data it can rely on.
SNOK MDM - Master Data Management
A single source of truth about customers, materials and suppliers - a management report the whole board trusts.
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Modern Data Stack
One version of the truth instead of conflicting reports - management reporting cut from days to hours.
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Databricks - Lakehouse Platform and ML/AI
Data and ML on a single platform - the end of the silo between data engineering and data science.
Learn moreCloud, integrations and Clean Core
We design cloud architecture, integrations and SAP extensions aligned with the Clean Core approach. We balance business requirements, security, maintenance costs and the solution's long-term scalability.
Microsoft Azure
A cloud migration with a calculated TCO - no bill higher than on-premise after the first year.
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Applications on SAP BTP
SAP extensions outside the core - an S/4HANA conversion without the pain of custom code.
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Integrations and APIs
No more manual copy-pasting of data - systems talk to each other in real time, with a full audit trail.
Learn moreBespoke applications and products
We build applications and digital products tailored to a specific business process. This approach works well wherever off-the-shelf solutions fall short, demand too many compromises, or don't give the organisation the flexibility it needs.
Bespoke applications
Functionality that can't be bought off the shelf - an MVP in 8-16 weeks, with the code and IP fully yours.
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SNOK.me - project portfolio
A problem visible in a project two weeks earlier - better team allocation and delay prediction.
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On-premise LLM + RAG
AI where the cloud is not an option - models and company knowledge within your own infrastructure.
Learn moreAn approach that works for us
We start by understanding the data, the processes and the business problem. We check which systems already exist, where inconsistencies arise, who is accountable for the data, and which processes need application, integration or analytics support.
On that basis, we prepare a map of actions. Sometimes the right recommendation is to tidy up a handful of key master data tables before starting a data warehouse, lakehouse or analytics application project. It can equally be a good project if it removes a real business bottleneck.
We design solutions around a measurable business outcome, not around delivering code, an integration or a data environment for its own sake. The application, warehouse or AI model needs to operate within a specific process, have an owner within the organisation, and be built on data that can be trusted.
Technology stack
The team's certifications in Microsoft Azure, SAP BTP, data engineering, custom development and enterprise systems confirm SNOK's readiness to deliver end-to-end application and data projects.
A chemical group after five acquisitions
Over five years, the client completed five acquisitions across three countries. After the latest acquisition, the board could no longer be confident that the reports presented at its meetings rested on consistent data definitions. We implemented centralised master data management with LLM-based deduplication. As a result, management reporting could be based on a single, consistent data source, understood across the whole organisation.
Read the full storyRelated case studies
Consistent master data after five acquisitions - without rebuilding source systems
A chemical group that completed five acquisitions across three countries within five years needed to organise master data coming from different companies and systems. Each acquired organisation brought its own catalogues of materials, suppliers, products and financial accounts, making group-level reporting and decision-making harder.
View case studyOne hundred thousand HR events a year - without manual process handling
One of the largest healthcare operators in Central Europe, employing staff across 21 countries, faced the challenge of scaling its HR processes further. Regulatory differences between countries, a growing headcount and an increasing number of HR events required organising and automating key processes.
View case study