Custom artificial intelligence (AI) software.
Many organizations see opportunities with AI, but get stuck in isolated experiments. Cube turns artificial intelligence into software that truly works seamlessly: integrated with your processes, your data, and the systems you already use. From strategy and integration to functional AI features, machine learning, and a secure data foundation. We design, build, and manage the components that make AI usable in your organization.
What is artificial intelligence (AI)?
Artificial intelligence software is software that performs tasks that normally require human intelligence: recognizing patterns, understanding language, making predictions, and making decisions independently within predetermined limits. Whereas traditional software follows fixed rules written by a developer, artificial intelligence software learns from data and improves over time. It is not a standalone product, but a collection of services that work together: AI agents and copilots that take on tasks, LLM integrations that connect language models to your own sources, workflow automation that keeps processes moving, an MCP server that manages secure access, and AI-powered features that make all of this usable in your software. Cube designs, builds, and manages these components on the systems organizations are already running, with security and compliance built in from the very first line of code.
What does AI software consist of?
AI Agents as Copilots
Agents who take on tasks independently within your workflows, and copilots who support employees while they remain in control. From customer inquiry to follow-up task. Exactly as far as you want them to go.
AI Strategy and Integration
The starting point: Where does AI truly add value in your organization, and how can it be securely integrated with your processes and data? From strategy and use cases to a concrete roadmap.
Have your MCP server built
Give AI controlled access to your systems and data without having to overhaul your architecture. The MCP server securely exposes your business logic to AI models.
LLM Integrations
Connect general and domain-specific language models to your own sources, using a smart prompt layer and retrieval (RAG). This way, AI works with your knowledge rather than just what a model has learned in the past.
Workflow automation
Connect systems directly via their APIs and integrate AI-driven decision-making where it adds value. Not a bot that mimics human clicking, but an integration at the level where your processes converge.
AI-powered features
Functional AI features that are seamlessly integrated into your software: an in-product assistant, a smart search feature, or an AI chatbot that handles frequently asked questions.
Cube as your (AI) software development partner.
We build custom software that fits the way your organization works, rather than the other way around. Not a off-the-shelf package that forces you to adapt your processes, but software that supports your processes and that your people can understand without a manual. We work with proven open-source technology and build custom solutions on top of it. This gives you a reliable foundation with the freedom to do what your situation requires, without being locked into a single vendor. With over ten years of experience and a structured approach, we know the pitfalls. We help you determine where technology makes a difference and where it doesn’t, and we’ll tell you if something isn’t worth the investment. We’re not a vendor who simply checks off a task; we’re a partner who works with you to build what you want to achieve and who stays with you once the software goes live.
AI agents and copilots that actually take over work.
A chatbot answers your questions. An agent takes action: they determine what steps are needed, carry them out, and make adjustments along the way. A copilot does the opposite and lets the human stay in control, for example by contributing to the process or suggesting the next step. Cube builds both, with clear limits on what they’re allowed to do on their own.
Start with the right use case.
The biggest pitfall with AI is starting with the technology instead of the problem. Together, we’ll identify which process in your organization currently takes the most time or has the highest error rate, and whether AI is the best solution for it. Sometimes the answer is a smart integration that doesn’t involve AI. That honesty will ultimately benefit you more than an impressive demo.
Secure access using an MCP server.
An AI model doesn’t know on its own what’s going on in your organization today. An MCP server changes that: it gives models controlled access to your systems and data, without requiring you to overhaul your architecture. Your existing software continues to function as usual, with an intelligent gateway in front of it that determines what an AI agent is allowed to access and when.
LLM integrations that work with your knowledge.
A language model only knows what was in its training data. We integrate general and domain-specific models with your own documents and systems, using a prompt layer and retrieval-augmented generation (RAG). This allows you to build internal assistants and knowledge bases that provide up-to-date, accurate answers, with logging and evaluation to ensure quality and explainability.
Processes that flow smoothly on their own.
Consider a request that has to pass through several hands. Without automation, someone has to manually enter the data into the next system, and everyone else has to wait until that’s done. With workflow automation, that data flows automatically from system to system, and a human only steps in when a decision really needs to be made. Cube integrates directly via the API into your own middleware, using AI-powered decision-making at critical points.
AI features that actually work, not just gimmicks.
Think of an in-product assistant that guides users through a form, a search function that understands what someone means, or an AI chatbot that handles frequently asked questions. Each feature solves a specific problem: working faster, making fewer mistakes, and making knowledge accessible to everyone who uses it.
The data foundation for all your AI.
Each of these components relies on the same foundation: your data. As long as that data is scattered across separate systems that don’t communicate with each other, AI will remain a promise rather than a reality. A Data Management Platform brings your data together in one place and makes it AI-ready. Agents extract context from it, LLM integrations draw from it via retrieval, and workflow automation uses it as a single source of truth. This gives your AI applications a reliable foundation, and you decide which data goes where, rather than letting the model guess.
Our approach: versatile and tailored to your needs.
At Cube, we see ourselves not just as a vendor, but as a true software development partner. We work with you to make strategic decisions, provide technological advice, and deliver solutions that make a real impact. Our approach is always tailored to your specific needs and goals. We actively contribute ideas and ensure that the technology we deliver not only works but also genuinely contributes to the growth and efficiency of your organization. From the initial ideas to the final implementation and optimization, we ensure that the solution is a perfect fit for your organization.
We help corporations operate like startups, and startups grow into corporations.
AI Advice in 30 Minutes
Wondering what AI can do for you? So are we.
Curious about what AI can do for your organization? Schedule a 30-minute meeting with Jarno. Together, we’ll explore which processes are suitable for AI and what the logical first step should be.
With courage, pragmatism, and a focus on quality.
Our team. Your team.
Amber Projectmanager
Bart Developer
Bernard Developer
Bob Test Engineer | Security & Privacy
Demi Officemanager
Dennis Full Stack Developer
Guus Full Stack Developer
Jarno Business Director
Jarno Back-end Developer
Jasper Developer
Jenne Digital Marketeer
Jeroen Back-end Developer
Job CEO | Executive
Joost Tech Lead | Team Pentagon
Jordy Software Architect
Justin Tech Lead | Team Hexagon
Kees Projectmanager
Kevin Developer
Laura Digital Designer
Maartje Content Marketeer
Mans Operations Manager
Marcus Projectmanager
Marleen Projectmanager | Team Lead Octagon
Mart Front-end Developer
Melanie Projectmanager | Team Lead Hexagon
Mick Tech Lead | Team Nexus
Nicky Projectmanager
Onno Business Controller
Remi Software Architect
Rogier Business Consultant
Rosan Manager People & Organization
Roy Full Stack Developer
Ruben Full Stack Developer
Ruben Digital Designer
Sander Developer
Stijn Front-end Developer
Tamara Business Consultant
Thomas Back-end Developer
Tom Tech Lead | Team Octagon
Wesley Projectmanager
Questions about AI? No problem.
Only as a conscious choice, not as the default. The cloud tools run in enterprise versions with IP protection, and it is determined in advance what data may be sent to external AI. If requirements are strict, self-hosted is an option.
A DMP ensures data is centralised and structured. MCP is the layer that gives AI models access to that data. They complement each other.
Yes, when implemented correctly. MCP runs on your own infrastructure. Cube always implements with permission management, authentication, and audit logging in line with ISO 27001.
Yes. We integrate agents and copilots into your existing systems via MCP, so your business logic remains intact. There’s no need to overhaul your architecture: the agent is granted targeted, controlled access to exactly the data and actions required for its task.
MCP is an open standard that enables AI models to communicate in a controlled way with external systems such as CRM, ERP, or internal databases. Originally developed by Anthropic, it is now governed by the Linux Foundation.
A copilot supports a person while they work and responds to direct input. An agent independently carries out a task, in multiple steps and across systems, within established parameters. The distinction lies in autonomy and human oversight, not in the technology.
Processes that are repetitive and rule-driven, involve digital input and output, have sufficient volume to justify the investment, and contain variations that AI can assess. Examples include request processing, booking flows, invoice recognition, and data transfer between systems.
No. The GitLab Duo Agent Platform is at the heart of our development environment, but we aren't tied to a single coding agent. We choose what works best for each situation and adapt when something better comes along, without vendor lock-in.