AI integration means enabling artificial intelligence to work together with your existing software, data, and processes. Cube integrates and implements AI into ERP, CRM, and custom systems, enabling organizations to make faster and more informed decisions without giving up control of their data. We handle everything from analysis to full implementation: securely and manageably.
Many organizations recognize the opportunities offered by AI, but in practice, it turns out to be more challenging than expected. Teams struggle with the question of which AI tools best fit their processes, and how they can deploy generic models without losing their organization’s specific knowledge. Data is scattered across various systems, and connecting it to AI for example, via a MCP server often feels like a complicated puzzle, with privacy, security, and compliance always looming in the background.
In addition, there is sometimes a lack of internal expertise to implement AI on a structural basis. Efforts remain limited to pilots and prototypes that never fully come to life, even though everyone senses that there is potential for added value. And even when an AI solution is up and running, the question arises of how to manage, monitor, and securely scale it without compromising processes or data.
Cube ensures that AI is not just valuable on paper, but actually works within your core processes. We connect AI to your existing systems so that it becomes a feature that is actually used and delivers results. In co-creation, we translate use cases into a technical design, build secure integrations and deliver iteratively via our OTAP street with GitLab boards, CI/CD, release policies and monitoring.
Your systems, our expertise.
The engine behind smart AI
We connect you to general-purpose and domain-specific LLMs and put a smart prompt layer over it. Think templates, system prompts, prompt routing and function calling to your backend or middleware. Everything is logged and evaluated, ensuring quality and explainability.
We unlock your documents and domain knowledge through retrieval-augmented generation (RAG). With embeddings, indexing and retrieval, we enrich content and build internal assistants and knowledge bases for employees and customers. This makes information always findable, understandable and up-to-date.
AI agents pick up tasks within workflows and communicate with internal systems such as CRM, ERP, DWH or process applications. We model tasks, guardrails and fallback paths, and deliver this as manageable services with clear release agreements. This way, you work through smoothly and safely.
We link classification, extraction, summarisation, translation and transcribe to forms, case flows and management screens in your portal or app. Employees have less manual work and turnaround times decrease, while quality increases.
We ensure that input and output always comply with policies and filters, including audit logging and data minimisation. We record agreements in the service package and SLA, so that management and support are clear.
Dashboards show performance, error rates and data flows. With SAST, dependency scans, uptime checks and release monitoring, you always know that everything is running as it should.
AI at Cube works like a smart teammate: it strengthens your processes, takes manual work out of your hands and leverages your data in a secure and insightful way.
Security and privacy are guaranteed from the start: our ISO 27001 and NEN7510 processes are periodically audited and form the foundation for compliant AI applications. This keeps management clear, you can trust releases and you know the solution is scalable for future applications. With Cube, AI becomes not an experiment, but a working feature that strengthens your core processes and delivers measurable value.
Imagine this: a customer requests a new application and you enter the requirements into an AI tool. An hour later, there is code that seemingly does what you wanted. That sounds tempting. But you will soon realise that something is missing: grip. Software development means building in privacy and security from the start, testing code automatically and building applications in a way that they can be managed and developed further. That requires readable code that a developer can understand and maintain.
Integrating AI into existing systems can be complicated. At Cube, we take a structured approach, giving you certainty about results, security and management from start to finish. Our approach ensures that AI does not get stuck in a few ideas, but rather realises the practical implementation, so that it actually adds value to your core processes.
We start with a sharp inventory: what is the scope, which user stories are important and what does the MVP look like? By drawing up context diagrams (C4), flow charts and a concrete project plan, we create a clear backlog for design and realisation. This way, you know exactly what is coming and what value you can expect.
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AI must fit within your existing IT landscape. We create both high-level and detailed designs and carefully examine all the necessary links, both with existing software within your organisation and with specific AI tools. This creates a solution that is secure, scalable, future-proof and optimally integrated with your current systems.
We deliver AI features in controlled releases, including acceptance environments, test scenarios and clear release agreements. This allows you to see initial results quickly, while we ensure quality and stability.
It doesn't stop after delivery. With a service package including response times, a service desk in GitLab, evaluations and a strip card for further development, you stay in control. Hosting can be on shared or dedicated cloud, including backups and failover, keeping everything running safely and reliably.
The result is a working AI feature that connects to your front-end application. With secure data links, monitoring and clear service agreements. You get visible value quickly and can then scale up in a controlled way, without compromising security or management.
Our AI integrations follow the same principles as our software: modular, scalable and safe. We combine proven open-source technology with high-code customization, so that AI works within your front-end applications and is linked to your DMP or other data sources. Machine learning and smart automations are built on a strong foundation, allowing you to innovate faster and get more value from your existing systems. This way, you maintain control over your data, rely less on big tech vendors and are ready for future innovations. The result? Working AI features that add value to your processes, support employees and improve decisions.
More efficient processes
Repetitive tasks are automated and workflows are faster and more fluid.
Better decisions
Data becomes insightful, instantly deployable and supports well-informed choices.
More time
Manual work is reduced, allowing employees to focus on valuable tasks.
Faster and personal service
Customers are offered relevant information quickly and consistently.
Reliable partner
Our dedicated AI team guides implementation, ensures secure integrations and continuous maintenance.
Measurable & scalable impact
Results are measurable. AI grows with your organisation and remains secure, manageable and compliant.
OpenAI is an advanced AI technology that can conduct conversations, answer complex questions and make information understandable. It helps organisations make knowledge accessible to employees and customers, turn data into actionable insights and handle routine queries automatically.
Gemini is an advanced AI platform that combines natural language and other data sources to automate and improve business processes. It can interpret information, perform analysis and perform tasks within different applications and workflows.
Claude (Anthropic) can process information and unlock knowledge without exposing or using sensitive data to train the AI model externally. This allows organisations to apply AI securely within internal tools, portals and business processes.
LangChain is a framework that enables language models to be linked to data sources, applications and workflows. It enables organisations to automate complex tasks, enrich knowledge bases and internal tools with AI, and make customer portals smarter.
n8n is an open-source workflow automation platform that allows you to easily connect different applications and data sources. It allows you to automate tasks and processes, synchronise data and build workflows that fit exactly the way your organisation works.
Orq is a workflow and process automation platform that makes complex business processes simple and reliably executable. It links different systems together, automates repetitive operations and ensures that information is always available at the right time.
LLaMA is an advanced language model that helps organisations understand, analyse and leverage large amounts of information.
Microsoft Copilot is an AI assistant built into familiar Microsoft 365 applications such as Word, Excel and Teams. It helps employees automate repetitive tasks, prepare documents and reports faster and analyse data instantly.
Curious to see what’s possible?
Not a ready-made package, but a solution tailored to your specific needs. Together with Jarno, you’ll explore what can be integrated securely and effectively.
With guts and a focus on quality.
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AI integration involves making artificial intelligence work together with your existing software, data, and processes. Instead of being a standalone tool, AI becomes part of your portals, apps, or ERP. This way, it supports your employees and improves decision-making without requiring you to rebuild your systems.
Yes. Cube integrates AI directly with existing ERP, CRM, and custom systems via the API. We first design the necessary integrations and build them modularly, so that AI operates within your current IT landscape rather than alongside it. This ensures your system remains manageable and scalable.
Your data remains yours. Cube builds AI integrations into its own middleware and connects them to your own data sources, ensuring that data doesn’t leak to external models. Everything is logged and made auditable, and we operate in accordance with ISO 27001 and NEN7510. This way, you maintain control over privacy, security, and compliance.
Start with the use case, not the tool. Cube begins with a brief assessment: What is the scope, which processes deliver value, and what does a feasible first version look like? From there, we build a concrete plan so that AI doesn’t get stuck in isolated experiments.
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That varies by project. Cube delivers in an iterative manner: a defined initial version (MVP) is often up and running within a few weeks to months, after which we expand it step by step. By working in short cycles, you’ll see results quickly and can make adjustments along the way. The costs depend on the scope, the number of integrations, and the data sources. During a no-obligation consultation, you’ll quickly get a realistic sense of the right direction for your situation.
